Research on Intelligent Decision Support System of Soybean
中科院自动化所的中英文新闻语料库
中科院自动化所的中英文新闻语料库中科院自动化所（Institute of Automation, Chinese Academy of Sciences）是中国科学院下属的一家研究机构，致力于开展自动化科学及其应用的研究。
该所的研究涵盖了从理论基础到技术创新的广泛领域，包括人工智能、机器人技术、自动控制、模式识别等。
下面将分别从中文和英文角度介绍该所的相关新闻语料。
[中文新闻语料]1. 中国科学院自动化所在人脸识别领域取得重大突破中国科学院自动化所的研究团队在人脸识别技术方面取得了重大突破。
通过深度学习算法和大规模数据集的训练，该研究团队成功地提高了人脸识别的准确性和稳定性，使其在安防、金融等领域得到广泛应用。
2. 中科院自动化所发布最新研究成果：基于机器学习的智能交通系统中科院自动化所发布了一项基于机器学习的智能交通系统研究成果。
通过对交通数据的收集和分析，研究团队开发了智能交通控制算法，能够优化交通流量，减少交通拥堵和时间浪费，提高交通效率。
3. 中国科学院自动化所举办国际学术研讨会中国科学院自动化所举办了一场国际学术研讨会，邀请了来自不同国家的自动化领域专家参加。
研讨会涵盖了人工智能、机器人技术、自动化控制等多个研究方向，旨在促进国际间的学术交流和合作。
4. 中科院自动化所签署合作协议，推动机器人技术的产业化发展中科院自动化所与一家著名机器人企业签署了合作协议，共同推动机器人技术的产业化发展。
合作内容包括技术研发、人才培养、市场推广等方面，旨在加强学界与工业界的合作，加速机器人技术的应用和推广。
5. 中国科学院自动化所获得国家科技进步一等奖中国科学院自动化所凭借在人工智能领域的重要研究成果荣获国家科技进步一等奖。
该研究成果在自动驾驶、物联网等领域具有重要应用价值，并对相关行业的创新和发展起到了积极推动作用。
[英文新闻语料]1. Institute of Automation, Chinese Academy of Sciences achievesa major breakthrough in face recognitionThe research team at the Institute of Automation, Chinese Academy of Sciences has made a major breakthrough in face recognition technology. Through training with deep learning algorithms and large-scale datasets, the research team has successfully improved the accuracy and stability of face recognition, which has been widely applied in areas such as security and finance.2. Institute of Automation, Chinese Academy of Sciences releases latest research on machine learning-based intelligent transportationsystemThe Institute of Automation, Chinese Academy of Sciences has released a research paper on a machine learning-based intelligent transportation system. By collecting and analyzing traffic data, the research team has developed intelligent traffic control algorithms that optimize traffic flow, reduce congestion, and minimize time wastage, thereby enhancing overall traffic efficiency.3. Institute of Automation, Chinese Academy of Sciences hosts international academic symposiumThe Institute of Automation, Chinese Academy of Sciences recently held an international academic symposium, inviting automation experts from different countries to participate. The symposium covered various research areas, including artificial intelligence, robotics, and automatic control, aiming to facilitate academic exchanges and collaborations on an international level.4. Institute of Automation, Chinese Academy of Sciences signs cooperation agreement to promote the industrialization of robotics technologyThe Institute of Automation, Chinese Academy of Sciences has signed a cooperation agreement with a renowned robotics company to jointly promote the industrialization of robotics technology. The cooperation includes areas such as technology research and development, talent cultivation, and market promotion, aiming to strengthen the collaboration between academia and industry and accelerate the application and popularization of robotics technology.5. Institute of Automation, Chinese Academy of Sciences receivesNational Science and Technology Progress Award (First Class) The Institute of Automation, Chinese Academy of Sciences has been awarded the National Science and Technology Progress Award (First Class) for its important research achievements in the field of artificial intelligence. The research outcomes have significant application value in areas such as autonomous driving and the Internet of Things, playing a proactive role in promoting innovation and development in related industries.。
煤矿掘进多行为协同控制智能决策模型
煤矿掘进多行为协同控制智能决策模型王宏伟1，2，4， 郄晨飞1，2， 付翔1，2， 李进1，4， 王浩然1，3（1. 太原理工大学 山西省煤矿智能装备工程研究中心，山西 太原 030024；2. 太原理工大学 矿业工程学院，山西 太原 030024；3. 太原理工大学 安全与应急管理工程学院，山西 太原 030024；4. 太原理工大学 机械与运载工程学院，山西 太原 030024）摘要：智能决策支持的掘进多行为协同控制是煤矿掘进工作面智能化的核心之一，掘进多行为协同控制的最优时序规划是智能决策的关键。
针对煤矿掘进多行为控制模式单一、固化、协同作业能力差等问题，设计了一种煤矿掘进多行为协同控制智能决策模型，实现了掘进多行为在最优时序下的协同作业。
首先，提出了掘进多行为协同控制智能决策方法，确定了掘进多行为可行时序规划集和多目标最优时序规划策略；其次，根据掘进现场的规定和工艺要求，确定了掘进动作事件集，通过对事件集中两两动作事件之间时间关系的分析，求出掘进多行为时间关系约束矩阵；然后，根据时间点关系约束矩阵转换方法，将掘进多行为时间关系约束矩阵转换为时间点关系约束矩阵，再求出掘进多行为可行时序规划集；最后，定义不同掘进目标下的求解函数，求得不同掘进目标的最优时序。
实验结果表明，在不同掘进目标下，按照模型决策出的掘进动作最优时序规划结果，掘进机器人可无干涉协同作业，且掘进作业1个工作循环的执行时间与决策模型计算的时间基本一致。
关键词：掘进工作面；协同作业；多行为协同控制；智能决策；最优时序规划；掘进动作事件集中图分类号：TD632 文献标志码：AIntelligent decision-making model of multi-behavior collaborative control in coal mine excavationWANG Hongwei 1,2,4, QIE Chenfei 1,2, FU Xiang 1,2, LI Jin 1,4, WANG Haoran 1,3(1. Center of Shanxi Engineering Research for Coal Mine Intelligent Equipment, Taiyuan University of Technology,Taiyuan 030024, China ； 2. College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024,China ； 3. College of Safety and Emergency Management Engineering, Taiyuan University of Technology,Taiyuan 030024, China ； 4. College of Mechanical and Vehicle Engineering, Taiyuan University of Technology,Taiyuan 030024, China)Abstract : Intelligent decision-making support for multi-behavior collaborative control in coal mine excavation is one of the core functions of the coal mine excavation working face. The optimal time series planning of multi-behavior collaborative control in excavation is the key to intelligent decision-making. In order to solve the problems of single control mode, solidification and poor collaborative operation capability of multi-behavior in coal mine excavation, an intelligent decision-making model of multi-behavior collaborative control in coal mine excavation is designed. It realizes the collaborative operation of multi-behavior in the optimal time series. Firstly,an intelligent decision-making method for excavation multi-behavior collaborative control is proposed. The feasible time series planning set and multi-objective optimal time series planning strategy for excavation multi-收稿日期：2023-05-08；修回日期：2023-06-15；责任编辑：胡娴。
万物互联英文文献
万物互联英文文献1. Title: Internet of Things: A review on enabling technologies, design challenges, and applicationsAuthors: Yan Zhang, Qinghua Zheng, Laurence T. YangPublished in: Journal of Industrial Information IntegrationAbstract: This paper presents a comprehensive review of enabling technologies, design challenges, and applications in the field of Internet of Things (IoT). The authors discuss various aspects such as IoT architecture, communication protocols, security and privacy issues, and various applications of IoT in healthcare, transportation, and smart cities.2. Title: A survey on Internet of Things architecturesAuthors: Antonio Jara, Miguel A. Zamora, Antonio F. Skarmeta Published in: Journal of Computers and Electrical Engineering Abstract: This paper provides a survey on different architectural approaches for implementing Internet of Things (IoT) systems. The authors discuss various architectures, including centralized, decentralized, and hybrid architectures, as well as the role of cloud computing in supporting IoT applications. The paper also highlights the challenges and future trends in IoT architecture design.3. Title: Machine learning in Internet of Things: a reviewAuthors: Guanglong Du, Shuangquan Wang, Guiwu WeiPublished in: Journal of Industrial Information IntegrationAbstract: This paper reviews the applications of machine learning techniques in the context of Internet of Things (IoT). The authors discuss how machine learning algorithms can be used to analyze and interpret the massive amount of data generated by IoTdevices, enabling intelligent decision-making and automation. The paper also discusses the challenges and future directions of machine learning in IoT.4. Title: Security and privacy in Internet of Things: A systematic literature reviewAuthors: Arpan Kumar Kar, Kumaraguru Ponnurangam, Pradeep Kumar KPublished in: Future Generation Computer SystemsAbstract: This paper presents a systematic literature review on security and privacy issues in the Internet of Things (IoT). The authors analyze various security and privacy concerns and propose solutions to mitigate them. The paper also discusses the challenges and future research directions in ensuring the security and privacy of IoT devices and systems.5. Title: Smart cities and Internet of Things: A systematic review Authors: Vipin Tyagi, Anand PaulPublished in: Journal of Grid ComputingAbstract: This paper reviews the concept of smart cities and the role of Internet of Things (IoT) in enabling smart city initiatives. The authors discuss various IoT-based applications in areas such as energy management, transportation, and healthcare in the context of smart cities. The paper also highlights the challenges and future prospects of implementing smart city initiatives using IoT technologies.。
AISSVOL5VOL1-AICIT
Contents:Editorial Board (i)Call for Papers (vi)< PART 1 >Solve Combinatorial Optimization Problem Using Improved Genetic Algorithm (1)Hanmin Liu, Qinghua Wu, Xuesong YanOptimization for the Row Heights in Medium-Length Hole Blasting Design by Genetic Algorithms (9)YANG Zhen, WANG Cheng-Jun, GUO LiAn Improved Differential Evolution with Adaptive Disturbance for Numerical Optimization .. 16 Dan MengA Radial Basis Function based Artificial Immune Recognition System for Classification (24)DENG Ze-lin, TAN Guan-zheng, HE PeiThe Forecasting Algorithm Based on User Access Intention (33)Jun Guo, Fang Liu, Yongming Yan, Bin ZhangPublicly Available Visualization System of Environmental Remote Sensing Information (40)Rustam Rakhimov Igorevich, Yang Dam Eo, Dugki Min, Mu Wook Pyeon, Ki Ho HongExamining Hospitality and Tourism Majors’ Intensions of Entering Hospitality and Tourism Professions Based on Theory of Planned Behavior (51)Ya-Ling Wu, Cheng-Wu Chen, Ya-Hui LiaoResearch Overview of Manifold Learning Algorithm (58)Wei Zhan, Guangming Dai, Hanmin LiuFormal Verification of Process Layer with Petri nets and Z (68)Yang Liu, Jinzhao Wu, Rong Zhao, Hao Yang, Zhiwei ZhangA Robust Text Zero-watermarking Algorithm based on Dependency Parsing (78)Yuling Liu, Ting JiangSimulation Modeling of Inter-firm Financial Contagion Process: a Network Perspective (86)WU BaoNew Cryptanalysis on 6-round Khazad (94)Yonglong TangA New Risk Assess Model for Urban Rail Transit Projects (104)Zhu Xiangdong, Xiao Xiang, Wu ChaoranAnt Colony Algorithm Optimized by Vaccination (111)He Haitao, Xin NingComputer Network Security and Precaution Evaluation based on Incremental Relevance Vector Machine Algorithm and ACO (120)Guangyuan SongRealization of an Embedded and Automated Performance Testing System for a MEMS Transducer (128)LIAO Hai-yang, XIONG Kui, WEN Zhi-yuMulti-level Cache Prediction and Partitioning Mechanism in CMP (135)Shuo Li, Gaochao Xu, Xiaozhong Geng, Xiaolin Qiao, Feng WuNew Classes of Sequences for Encryption Procedures in Symmetric Cryptography (145)Amparo Fuster-SabaterExplore and Analysis of Environmental Policy Based on Green Industry Development (152)Chunhong Zhu, Zhe Liu, Yue Zhou, Xuehua ZhangResearch on Service Encapsulation of Manufacturing Resources Based on SOOA (158)Lingjun Kong, Wensheng Xu, Nan Li, Jianzhong ChaA Twice Ant Colony Algorithm Based on Simulated Annealing for Solving Multi-constraints QoS Unicast Routing (167)Yongteng Lv, Yongshan Liu, Wei Chen, Xuehui Shang, Yuanyuan Han, Chang LiuA Two-phase Multi-Constraint Web Service Selection Approach for Web Service Composition (176)Zhongjun Liang, Hua Zou, Fangchun Yang, Rongheng LinAdvanced Coupled Map Lattice Model for the Cascading Failure on Urban Street Network . 186 ZHENG Li, SONG Rui, Xiao YunTransition Probability Matrix Based Tourists Flow Prediction (194)Yuting Hu, Rong Xie, Wenjun ZhangA Study on the Macro-Control Policy of China Real Estate Development (202)Lu ShiAn Effective Construction of a Class of Hyper-Bent Functions (212)Yu Lou, Feng Zhou, Chunming TangSpeaker-independent Recognition by Using Mel Frequency Cepstrum Coefficient and Multi-dimensional Space Bionic Pattern Recognition (221)Guanglin Xian, Guangming XianIntelligent Decision Support System (IDSS) for Cooling/Heating Sources Scheme Selection of City Buildings Based on AHP Method (228)Liu Ying, Jiang Kun, Jiang ShaModeling of Underwater Distributed Target Based on FDTD and Its Scale Characteristic Extraction (237)P AN Yu-Cheng, SHAO Jie, ZHAO Wei-Song, ZHONG Ya-QinMethod for Dynamic Multiple Attribute Decision Making under Interval Uncertainty and its Application to Supplier Selection (246)Xu JingStudy on Multi-Agent Information Retrieval Based on Concern Domain (254)Sun JianmingA New Method for Solving Numerical Solution of Fractional Differential Equations (263)Jianping Liu, Xia Li, HuiQuan Ma, XueZhi Mao Guoping ZhenAssessment and Analysis of Hierarchical and Progressive Bilingual English Education Based on Neuro-Fuzzy approach (269)Hao Xin< PART 2 >Computer-based Case Simulations in China: 2001-2011 (277)Tianming Zuo, Peng Wang, Baozhi Sun, Jin Shi, Yang Zhang, Hongran BiHybrid Monte Carlo Sampling Implementation of Bayesian Support Vector Machine (284)Zhou Yatong, Li Jin, Liu LongA Face Recognition Method based on PCA and GEP (291)WANG Xue-guang, CHEN Shu-hongResearch and Application of Higher Vocational College Library Personalized Information Service Based on Cloud Computing (298)Meiying Nie, XinJuan Zhou，Qingzhi WenA Calculation Model for the Rover’s Coverage Boundary on the Lunar Surface Based on Elevation (307)Hu Yasi, Meng Xin, Pan Zhongshi, Li Dalin, Liang Junmin, Yang YiAn Evaluation of firms’ Best Strategies with the ANP, AHP and Sensitivity Test Approaches 316 Catherine W. Kuo, Shun-Chiao ChangDesign of Embedded Vehicle Safety Monitoring System (326)Jing-Lian, Lin-Hui Li, Hu-Han, Ya-Fu Zhou, Feng-Hu, Ze-Quan ZengThe Approach to Obtain the Accurate TOA of VHF Lightning Signals Based on FastICA Algorithm (334)Xuquan Chen, Wenguang ZhaoIntegrating Augmented Reality into Consumer’ Tattoo Try-on Experience (341)Wen-Cheng Wang, Hao-Hsiang Ku, Yen-Wu TiResearch on Location for Emergency Logistics Center Based on Node Cost (348)Wang ShouqiangLogistics Terminal Facility Location Model Based on Customer Value in Competitive Environment (354)Han Shuang Wang XiaoxiaA Decision Support Model for Risk Analysis with Interval-valued Intuitionistic Fuzzy Information (362)Guoqing WuPeak to Average Power Ratio Reduction with Bacterial Foraging Algorithm for OFDM Systems (370)Jing Gao, Jinkuan Wang, Bin WangUsing Linear and Nonlinear Inversion Algorithm Combined with Simple Dislocation Model Inversion of Coal Mine Subsidence Mechanism (379)Yu-Feng ZHU，Qin-Wei WU，Tie-Ding Lu, Yan LuoApplication of Multi- media in Education of Schoolgirl’s Public P. E. in College and University—set Popular Aerobics as Example (388)Yuanchao zhouA Fuzzy Control System for Trailers Driven by Multiple Motors in Side Slipway to Launch and Pull Out Ships (395)Nyan Win Aung, Wei HaijunA Novel Image Encryption Algorithm based on Virtual Optical Imaging and Hyper-chaos .. 403 Wei Zhu , Geng Yang, Lei Chen, Zheng-Yu ChenThe Structure Character of Market Sale Price in the Coordinating Supply Chain (412)Jun Tian, Zhichao WangDesign Parameter Analysis for Inducers (419)Wei Li, Weidong Shi, Zhongyong Pan, Xiaoping Jiang, Ling ZhouAutomatic Recognition of Chinese Traffic Police Gesture Based on Max-Covering Scheme .. 428 Fan Guo, Jin Tang, Zixing CaiDetermination of Acrylamide Contents in Fried Potato Chips Based on Colour Measurement 437 Peng He, Xiao-Qing Wan, Zhen zhou, Cheng-Lin WangAn Efficient Method of Secure Startup and Recovery for Linux (446)Lili Wu, Jingchao Liu,Research on Life Signals Detection Based on Parallel Filter Bank and Higher Order Statistics (454)Jian-Jun LiResearch for Enterprise Logistics Dynamic Optimization Based on the Condition of Production Ability Limited (462)Guo QiangTechnological Progress in Macroeconomic Volatility and Employment Impact analysis - Based on Endogenous Labor RBC Model (469)Wang Qine, Hu honghaiResearch on Bottleneck Identification in Multiple Products Small lot Production Logistics of Manufacturing Enterprise Based on TOC (476)Jian Xu, Hongbo WangThe Spiral Driven and Control Method Research of the Pipe Cleaning Robot (484)Quanyu Yu, Jingyuan Yu, Jun Wang, Jie LiuHoisting Equipment of Coal mine Condition Monitoring and Early Warning Based on BP Neural Network (491)Shu-Fang Zhao, Li-Chao ChenSpatial Temporal Index-based Historic Closing Event Query or Moving Objects (497)Xianbiao Ji, Hong Mi, Zheping ShaoResearch on the Risk-sharing Mechanism of Energy Management Contract Project in Building Sector (510)CaiWeiguang, Ren Hong, Qin BeibeiFinancial Crisis and Financial Index Structure Break (516)Keng-Hsin Lo, Yen-Chang Chen, Yi -Wei ChuangThe Research of Cooling System for the High-Energy Storage Flywheel (522)Wang Wan, He LinNumerical Models and Seismic Design of Steel Frames Equipped with Supplemental Fluid Viscous Devices (528)Marco ValenteStudy on Positive and Dynamic Enterprise Crisis Management based on Sustainable Business Model Innovation (535)Shi-chang Fu, Hui-fen Wang, Dalen ChiangQuantitatively Study on the Mechanism of Cooperating Profit Distribution within Business Ecosystem (544)Bin HuStudy on the Landscape Design of Urban Commemorative Squares Based on Sustainable Development (552)Wenting Wu, Ying Li, Yi Ren< PART 3 >SRPMS: A web-based Project Management System for Scientific Research (559)Yanbao Ji, Xiaopeng Yun, Zhao Jun, Quanjiang Bai, Lingwang GaoEmpirical Study on Influence Factors of Carbon Dioxide Emissions in Liaoning Province based on PLS (567)Yu-xi Jiang, Su-yan He, Xiang-chao WeiHarmony Factor Considered Evaluation of Science Popularization Talents Based on Grey Relational Analysis Model (575)Li MingStudy on the Safety of High-Speed Trains under Crosswind (582)Xian-Liang Sun, Bin-Jie Wang, Ming Gong, San-San Ding, Ai-Qing TianControl Method of Giant Magnetostrictive Precise Actuator Based on the Preisach Hysteresis Theory (589)Yu Zhang, Huifang Liu, Feng SunDynamic Modeling and Characteristics Analysis of Rolls along Axial Direction for Four High Mill Based on Timoshenko Theory (602)Jian-Liang Sun, Yan PengConstruct on Maintenance Requirement Analysis Model of Pavement Management System 610 Xiu-shan Wang, Yun-fang YangAutomatically Generate Test Data Based on Intelligent Algorithms Method (617)Jian Ni, Ning-NingYangAnalysis of the Functions of a High-Speed Railway Station in China (623)Li-Juan Wang, Tian-Wei Zhang, Fan Wang, Qing-Dong ZhouEconometric Analysis of Expectation in Savings-to-Investment in Capital Market Converting Process (630)Wang Yantao , Yu Lihua ,Mao BeibeiAnalysis Model and Empirical Research on Product Innovation Process of Manufacturing Enterprises Based on Entropy-Topsis Method (637)Hang Yin, Bai-Zhou Li, Tao Guo, Jian-Xin ZhuThe Market Analysis and Prediction of Chinese Iron and Steel Industry (645)Li Xiaohan, Sun Qiubai , Li HuaSystem Dynamics Mode Construction and System Simulation in the Product Innovation Process (653)Jian-Xin Zhu, Jun DuResearch on Organization Innovation of Enterprise Based on Complexity Theory (664)Yu Zheng, Tao GuoThe Study on TFP of Iron and Steel Industry inChina Based on DEA-Malmquist Productivity Index Model (672)Xiaodong Dong, Yuzhi ShenResearch and Implementation of Energy Balance Control System in Metallurgy Industry (681)Qiu DongA Study of Opportunities and Threats in the Implementation of International Marketing for Production Design of Corporate Brand Licensing – A Case Study of POP 3D Co., Ltd. (689)Min-Wei Hsu，Tsai-Yun Lo，Liang,K.C.Research on Risk Forming Mechanism and Comprehensive Evaluation of the Enterprise Group (695)Dayong XUMode Construction of Dining Reform in Universities Based on Theory of Institutional Transformation (704)Li PingjinResearch on QR Decomposition and Algorithm of Linguistic Judgment Matrix (711)Lu YuanA Comparison of the Mahalanobis-Taguchi System to A Selective Naïve Bayesian Algorithm for Semiconductor Chemical Vapor Deposition Process (720)Jui-Chin Jiang, Tai-Ying LinStudy of Policy-making Model for Producer Service: Empirical Research in Harbin (730)Xin Xu, Yunlong DingKrein space H∞ filtering for initial alignment of SINS with large azimuth misalignment (738)Jin Feng, Fei Yu, 3Meikui Zou, Heming JiaInternet Word-Of-Mouth on Consumer Online Purchasing Behavior Analysis in China (747)Jie Gao, Weiling YeConvex Relaxation for Array Gain/Phase Calibration in ULAs and UCAs with Unknown Mutual Coupling (758)Shu CaiFinancial-Industrial Integration Risk Management Model of Listed Companies Base on Logistic (767)Ke WenBehavior Equilibrium Analysis for The Cross-Organizational Business Process Reengineering in Supply Chain (775)Jianfeng Li, Yan ChenA Secure Scheme with Precoding Approach in Wireless Sensor Networks (782)Bin Wang, Xiao Wang, Wangmei GuoA New Method on Fault Line Detection for Distribution Network (789)Bo LiManagers’ Power and Earnings Manipulating Preference (796)J. Sun, X. F. Ju, Y. M. Peng, Y. ChangStudy and Application of the Consistency of Distributed Heterogeneous Database Based on Mobile Agent (804)Zhongchun Fang, Hairong Li, Xuyan Tu。
智能交通系统中车辆路径优化问题的研究的开题报告
智能交通系统中车辆路径优化问题的研究的开题报告一、研究背景随着城市化进程的不断加快，城市交通问题愈发突出。
智能交通系统的出现解决了交通拥堵、事故频发和能源浪费等城市交通问题，其中车辆路径优化问题在智能交通系统中占有重要地位。
车辆路径优化问题是指寻找最短路径或最优路径，使车辆在尽可能短的时间内从起点到达终点。
因此，车辆路径优化问题的研究对于提高城市交通的效率、保证交通安全和节省能源具有重要的意义。
二、研究目的本研究将从实际应用角度出发，对车辆路径优化问题进行研究。
具体来说，主要包括以下几个方面：1. 分析车辆路径优化问题的研究现状和重要性；2. 探讨车辆路径优化中的影响因素及其作用；3. 统计分析车辆行驶数据，针对实际问题提出车辆路径优化算法；4. 通过仿真实验验证车辆路径优化算法的有效性和可行性；5. 提出未来进一步研究方向，为城市交通的智能化、高效化和可持续发展提供参考。
三、研究内容本研究的重点是车辆路径优化问题。
具体来说，主要包括以下内容：1. 对现有的车辆路径优化算法进行综述和分析，总结其优点和不足之处；2. 采用数学建模的方法，分析车辆路径优化中的影响因素；3. 提出一种基于深度学习的车辆路径规划算法，通过学习大量车辆行驶数据，优化路径规划结果；4. 通过场景模拟和实际测试，评估所提出算法的效果和可行性，与其他常用算法进行对比；5. 在以上研究基础上，结合实际应用场景，提出未来车辆路径规划的发展方向并进行展望。
四、研究方法本研究主要采用理论分析和仿真实验的方法。
具体来说，主要包括以下几个环节：1. 对车辆路径优化问题进行建模和理论分析，探讨各种影响因素的内在联系；2. 对大规模的车辆行驶数据进行分析和处理，提取有用的信息；3. 采用深度学习的方法，对车辆路径进行学习和优化；4. 基于仿真软件，进行大规模场景的仿真测试，并与其他常用算法进行对比；5. 实际测试并对所提出算法进行改进和优化。
智能制造英文版
智能制造英文版．Intelligent manufacturingAn overviewIntelligent manufacturing deep inartificial intelligence research. Generallythink that intelligence is the sum of knowledge and intelligence, the former is thebasis of intelligence, the latter is the ability to acquire and apply knowledge tosolve. Intelligent manufacturing shouldcontain intelligent manufacturing technologyand intelligent manufacturing system. The intelligence technique of manufacture is refers using the computer simulation marks intelligent activities suchas expert's analysis, judgment, inference,idea and decision-making and so on, and fusesorganically these intelligent activity andthe intelligent machine, applies its penetration in entire manufacture enterprise's each subsystem (e.g. management decision-making, purchase, product design, productive plan, manufacture,assembly, quality assurance and market saleand so on).Realizes the entiremanufacturehighlyoperation the manage to enterpriseflexibility and integration, thus substitutes or extends in the manufactureenvironment expert's partial mental labor,and carries on the collection, the memory, theconsummation, sharing, the inheritance andthe development of the manufacturing industryexpert's intelligent information, enhancesthe production efficiency enormously and theadvanced technique of manufacture.The intelligent manufacture system isrefers based on IMT (intelligent manufacturing technology), by the computersynthesis application artificial intelligence technology (e.g.artificialneural networks, genetic algorithm and so on),the intelligence manufacture machine,theagent technology, the parallel projects, thelife sciences and the systems engineeringtheory and the method, in the internationalstandardization and interchangeable foundation, causes the entire enterprise tomake each subsystem to intellectualize separately, and causes the manufacture systemto form by the network integrates, the highautomated one king of manufacture system.Intelligent manufacturing system can notonly in practice constantly enrich theknowledge base, have the function of self-learning, and collecting and understanding of environmental informationand its information, analysis and judgmentand the ability to plan their actions. The basic principleStarting from the essential feature of intelligent manufacturing system in distributed manufacturing network environment, according to the basic idea ofdistributed integration,In the applicationof distributed artificial intelligence theory and method of multi Agent system, realize flexible manufacturing unit of theintelligent and flexible manufacturing system based on network intelligent integration. According to the characteristics of the distribution system ofisomorphism in a local area forms for realizing intelligent manufacturing systemthereflects also actual the on basedinternet-based global manufacturing the realization of the intelligent manufacturingsystem model under the network environment.The overall idea of distributed IMS network:IMS is the essential characteristics of the individual manufacturing unit ofautonomy and the system as a wholeself-organizing ability, its basic patternis distributed more intelligent system. Basedon this understanding, and considering theinternet-based global manufacturing networkenvironment, we put forward the Agent baseddistributed IMS network's basic idea, as shown in figure 1. On the one hand, throughthe Agent give autonomy to each manufacturingunit, making it a fully functional, autonomy,an independent entity; On the other hand,through the coordination and cooperationbetween the Agent, gives systemself-organization ability.Multi Agent system implementation patternof the system is easy to design, implementation and maintenance, reduce thecomplexity of the system, enhance the system's restructuring, scalability and reliability, and improve theflexibility,adaptability and agility of the system. Based on the above framework, combinedwith the CNC machining system, developmentand application of distributed network prototype system by system manager, missionplanning, design and producers of fournodes.Systems manager node including two database server, database server and Agentsystem is responsible for the management ofthe entire global database, available foraccess of nodes in the prototype system fordata query, read, storage and retrieval operations, and for each node for data exchange and sharing, to provide a publicsystem, the Agent is responsible for the system in the network and the external interaction, through the Web server on theInternet home page of the system, users canaccess online home page the information related to obtaining the system, anddecideto needs, own their to accordingwhether the system is to meet these requirements, the system of the Agent is alsoresponsible for monitoring the interactionsbetween the various nodes on prototypesystem,such as record and real-time display of sending and receiving messages between nodes,task execution, etc.Mission planning nodes by the task manager and its Agent (task manager Agent),its main function is to task planning, fromthe Internet is decomposed into several subtasks, and then through the way of bidding,bidding to the task allocation of each node.Design node by CAD tools and its proxyAgent (design), it provides a good man-machine interface so that designers caneffectively and computer interaction, commonto complete the design task. CAD tools to helpdesign personnel according to user requirements for product design; Designed theAgent is responsible for online registration,cancellation registration, database management, interaction with other nodes,decide whether to accept the design task andsubmit a task to task the sender. Producers node is actually the project research and development of an intelligentmanufacturing system (intelligent manufacturing unit), including processingcenter and its network proxy Agent (machine).The intelligent adaptive machining centerconfiguration. The CNC system is controlledby intelligent controller processing process,to give full play to the processing of automated processing equipment potential,improve processing efficiency; Have certainability of self diagnose and self repair, inorder to improve the processing the reliability and safety of the equipment operation; Have the ability to interact withthe external environment; With open architecture to support the system integration and extension.The prototype system work:Every node in the system must be registeredthrough the network, to become the formalmember of the prototype system to obtainthecollaborateto privileges, correspondingwith other nodes in the system, common tocomplete the system task. The whole processof operation of the prototype system is asfollows:(1) any network user can access theprototype system of the home page for information about the system, but also through the fill out and submit user orderform provided by the system home page issuedorders to the system;(2) if received and accept the network user's orders, Agent system is to be deposited in the global database, from the global database, missionplanning nodes can take out the order, missionplanning, the task decomposition into severalsubtasks, and assign these subtasks prototypesystem access nodes;(3) product design subtasks are assigned to design node,the nodethrough good human-computer interaction tocomplete product design sub-tasks, generatethe corresponding CAD/CAPP data and documents,and nc code, and these data and documents inthe global database, finally submit the subtasks to mission planning nodes;(4) producers,to assigned are subtasks processingonce the subtasks was accepted by the producers nodes, machine Agent will be allowed to read the necessary data from theglobal database, and to transfer the data tothe processing center, processing center,according to these data and command to finishprocessing the subtasks, and the running status information transmitted to the machineAgent, machine Agent returns the result to themission planning nodes, submit the subtask;(5) in the system during the running of thewhole, the Agent is the interaction betweenthe various nodes in the system for recording,such as message sending and receiving, aglobal database data read and write, query thenode name, type, address, ability, and taskcompletion, etc.(6) Network client can understand order execution and results.The developmentIntelligent manufacturing deep inartificial intelligence research. Artificialintelligence is the intelligence of implementation of using artificial method onthe computer.Of complicated as the WanShanHuaand the structure of the product performanceand refinement, as well as the function ofdiversification, prompting a surge in productdesign information and process informationcontained, with internal information flowincrease of production line and productionequipment, manufacturing process andmanagement information must also soared, ahotspot and frontier, and thus prompt thedevelopment of manufacturing technology toimprove manufacturing system for the explosive growth of manufacturing information processing ability, efficiencyand scale. At present, the advanced manufacture equipment left the informationinput cannot operate, flexible manufacturingsystem (FMS) once they are cut off the sourceof information will immediately cease to work.Expert thinks, the manufacturing system isdriven by the original energy intoinformation driven, this requires a flexiblemanufacturing system requires not only, butalso show that the intelligent, otherwise itis difficult to deal with such a large amountof workload and complex information. Secondly,the complex environment of rapidly changingmarket demand and fierce competition, alsocalled for the manufacturing system showedhigher flexibility, agility and intelligence.Across the world, although the overall intelligent manufacturing was still in thestage of conceptual and experimental, butgovernments are included in the national development plans, this push to implement. In1992 the implementation of new technologypolicy and support by the President said thekey to the important technical (Critical Techniloty), including information technology and new manufacturing technology,ease of intelligent manufacturing technology,the U.S. government hopes the move to transform traditional industry andstart anew industry.Canada's 1994 ~ 1998 development strategyplan, think the future knowledgeintensiveindustry is driving the global economy anddevelopmenteconomic of basis the Canada,thought is very important to development andapplication of intelligent system, and putthe specific research project selection forintelligent computer, man-machine interface,mechanical sensor, the robot control systemintegration, the new device, the dynamic environment.Japan's in 1989, intelligent manufacturing system is proposed and launchedin 1994, the advanced manufacturing international cooperation research projects,including the companies to integrate and global manufacturing, manufacturing knowledge system, distributedintelligentcontrol system, rapid product realization ofdistributed intelligent system technology,etc.Research of information technology in theEuropean Union ESPRIT project, the project isfunded by the market potential of informationtechnology. 1994 and the start of the new R&Dproject, select the 39 core technologies, ofwhich three (information technology, manufacturingadvanced and biology moleculartechnology) are highlights the intelligentmanufacturing location.China at the end of the 80's willintelligent simulation the main issue inthe national science and technology development planning, understanding has madea number of achievements in the expert system,pattern recognition, robotics, Chinese machine. Recently, the State Ministry of science and technology put forward formallyindustrial intelligent engineering, as animportant part of the innovation ability oftechnology innovation project construction,intelligent manufacturing will be an important content of the project. Thus, the intelligent manufacturing is arising in the world, it is the developmentof manufacturing technology, especially theinevitable manufacturing development of information technology, is the result of thedevelopment of automation and integrationtechnology in depth.Integrated featuressystemmanufacture traditional the Withcompares, IMS has following several characteristics:(1) From organization abilityIn the IMS, each kind of composition unitcan according to the work duty need, voluntarily build up one kind of ultra flexible best structure, and defers to themost superior way movement. Not only its flexibility displays in the movement way, butalso displays in the structural style. Aftercompleting the task, this structure dismissesvoluntarily, prepares in the next duty buildsup a new kind of structure. The voluntarilyorganization ability is an IMS important symbol.(2) Autonomy abilityIMS has the abilities such as collectionand the understanding the environmental information and own information, and carrieson the analysis to judge and to plan own behavior ability. The powerful knowledgelibrary and based on the knowledge modelisthe autonomy ability foundation. IMS canactworkown and environment the to accordingcondition information to carries on the monitor and processing, and according to theprocessing finally self-adjusting controlstrategy, uses the best movement plan. Thiskind of autonomy ability causes the entiremanufacture system to have the anti jamming,auto-adapted and fault-tolerant and so on.(3) The ability of self-study and maintenanceIMS can take the original expert knowledge as the foundation, in reality carries on the study unceasingly, the perfectsystem knowledge library, and deletes theunsuitable knowledge in the storehouse, causes the knowledge library to hasten reasonably. At the same time, it also can carry on the self-diagnosis, the eliminationand repairing to the system failure. Thekindof character enables IMS to optimize and toadapt to each kind of complex circumstances.(4) Entire manufacture systemintelligentintegrationWhile IMS emphasized each subsystem intellectualization, pays great attention tointelligentthe system manufacture entire theintegration. This is the basic differencebetween IMS and “the intellectualized isolated” which specially applied in themanufacture process. IMS contains each subsystem, and integrates them in a whole,realizes the whole intellectualization.(5) Man-machine integrationintelligencesystemIMS is not a pure the artificial intelligence the system, but is theman-machine integration intelligence system,is one kind of mix intelligence. On the onehand, the man-machine integration prominentperson's core status in manufacture system,simultaneously under the intelligent machinecoordination, well has displayed human'spotential, causes between theman-machine todisplay one kind of equality to work togetheras colleagues,“understands” mutually, cooperates mutually relations, causes them toreveal respectively in the different level,complements each other. Therefore, inIMS,the high quality, the high intelligent personmachinethe role, better a play willintelligence and human's wisdom integrationof machinery Mechatronics issue can integratetruly in together.In summary, we may view IMS as one kind ofpattern, it is the collection of automation,flexibility, integration and intellectualization in a body, and unceasingly to depth development advancedmanufacture system.(6) Virtual realityThis technology supports the realizationhypothesized manufacture, also realizes oneof high level man-machine integration. Theman-machine union is a new generation of intelligent contact surface, causes the available hypothesized method with intelligent performance into reality, it isa dominant character of intelligent manufacture.Future development1、Artificial intelligence technology. Since the goal of IMS is computer simulation of intelligence activities ofmanufacturing human experts, partial mentallabor to replace or extension of the people,so the artificial intelligence technology hasbecome one of the key technology of IMS.IMSand artificial intelligence technology (expert system, artificial neural network,fuzzy logic) is closely related to.2、Concurrent engineering.In view of the manufacturing, concurrentengineering is an important technical method,used in IMS, will reduce the repetition blindness and the design of the product design.3、Information network technology.Information network technology is theprocess of manufacturing system and each linkintelligent support. The information network is also the manufacturing informationand knowledge flow channel.4、The virtual manufacturing technology.Virtual manufacturing technology cansimulate the entire life cycle of product inthe product design stage, thus the more effective, more economical, more flexibleproductthe production, of organizationdevelopment cycle is short, the product costis the lowest, the optimal product quality,production efficiency is the highestassurance. At the same time, the virtual manufacturing technology is theprerequisitefor the engineering realization of parallel.5、Discipline construction.Collect and understand the environmentinformation and its information and analysisjudgment and plan their behavior. Strong knowledge base and knowledge based model isthe basis of self-discipline.6、Man-machine integration.Intelligent manufacturing system is notonly the artificial intelligence system, andhuman-machine intelligent system, is a kindof hybrid intelligent. Want to completelyreplace human intelligence artificialintelligence expert in manufacturing process,analysis, judgement, decision independentlyundertake the task, at present is not realistic. Humachine highlighted the coreposition in manufacturing system, combinedofplay better machines, intelligent withhuman potential, to achieve a kind of collaborative working relationship of equality, so that the two made at different。
Intelligent Decision Support System
基于Web的DSS通过“瘦客户端”Web浏览器向管理者或 商情分析者提供决策支持信 息或者决策支持工具，浏览器包括可以访问全球网或公司内部网的诸如 Netscape Navigator 或者Internet Explorer。 运行DSS应用程序的服务器通过TCP/IP协议与用 户计算机建立网络连接。 基于Web的DSS可以是通讯驱动，数据驱动，文件驱动，知 识驱动，模型驱动， 或者混合类型。Web技术可用以实现任何类型ulation-Based DSS
Simulation-Based DSS deliver decision support information Simulationor decision support tools to help managers analyze semisemi-structured problems through simulation.
Data1. Data-Driven DSS
DataData-driven DSS is a type of DSS that emphasizes access to and timemanipulation of a time-series of internal company data and sometimes external data. Geographic Information Systems (GIS) are Dataspecial purpose Data-Driven DSS.
英文research proposal 标题
英文research proposal 标题The Impact of Artificial Intelligence on the Future of HealthcareArtificial intelligence (AI) has been revolutionizing various industries, and the healthcare sector is no exception. As the world grapples with an aging population, rising healthcare costs, and the need for more efficient and personalized care, AI has emerged as a promising solution to address these challenges. This research proposal aims to explore the potential impact of AI on the future of healthcare, focusing on its applications, the benefits it can offer, and the ethical considerations that must be addressed.The rapid advancements in AI, including machine learning, deep learning, and natural language processing, have already begun to transform the healthcare landscape. AI-powered technologies can assist healthcare professionals in various tasks, from disease diagnosis and drug development to patient monitoring and decision-making support. By leveraging large datasets, AI algorithms can identify patterns, detect anomalies, and make predictions with a level of accuracy and speed that surpasses human capabilities.One of the key areas where AI is expected to have a significant impact is in disease diagnosis and treatment. AI-based systems can analyze medical images, such as X-rays, CT scans, and MRI scans, with greater precision and speed than human experts, leading to earlier detection of diseases and more accurate diagnoses. This can lead to more timely interventions, improved patient outcomes, and reduced healthcare costs. Moreover, AI can assist in the development of personalized treatment plans by analyzing an individual's genetic and medical data to tailor therapies to their specific needs.Another promising application of AI in healthcare is in the field of drug discovery and development. The process of developing new drugs is costly, time-consuming, and often has a high failure rate. AI-powered tools can accelerate this process by identifying promising drug candidates, streamlining clinical trials, and predicting drug interactions and side effects. This can lead to the development of more effective and safer medications, ultimately improving patient care and reducing the burden on healthcare systems.Furthermore, AI can play a crucial role in improving patient outcomes and reducing healthcare costs by enhancing patient monitoring and care coordination. AI-powered wearable devices and remote monitoring systems can continuously gather and analyze patient data, alerting healthcare providers to potential health issuesor medication non-compliance. This can enable early intervention, prevent complications, and reduce hospital readmissions, leading to better patient outcomes and more efficient utilization of healthcare resources.While the potential benefits of AI in healthcare are significant, it is essential to address the ethical considerations and challenges that arise with the implementation of this technology. Issues such as data privacy, algorithmic bias, and the need for transparency and accountability in AI-based decision-making must be carefully navigated. Researchers and healthcare providers must work collaboratively to ensure that the development and deployment of AI technologies in healthcare are aligned with ethical principles and respect the rights and well-being of patients.Additionally, the integration of AI into healthcare will have implications for the workforce, as certain tasks and roles may be automated or transformed. It is crucial to consider the impact on healthcare professionals, such as radiologists, pathologists, and nurses, and develop strategies to retrain and upskill the workforce to adapt to the changing landscape.In conclusion, the impact of AI on the future of healthcare is poised to be profound. By leveraging the power of AI, the healthcare sector can improve disease diagnosis, accelerate drug discovery, enhancepatient monitoring and care coordination, and ultimately deliver more personalized and effective healthcare solutions. However, the successful integration of AI into healthcare will require a multifaceted approach that addresses the technical, ethical, and workforce-related challenges. This research proposal aims to contribute to the understanding of the impact of AI on healthcare and provide insights that can guide the responsible and effective implementation of this transformative technology.。
信息技术导论英语
信息技术导论英语Information technology (IT) has become an integral part of our daily lives, revolutionizing the way we communicate, work, and access information. This diverse field encompasses a wide range of domains, including computer hardware and software, networking, cybersecurity, data management, and artificial intelligence, among others. At its core, IT aims to develop and utilize technological solutions to enhance productivity, efficiency, and connectivity across various sectors.One of the most significant impacts of IT is the transformation of communication. The advent of the internet and digital communication platforms has shrunk the world, allowing individuals and organizations to connect and collaborate seamlessly across geographical boundaries. Email, instant messaging, video conferencing, and social media have become indispensable tools for personal and professional interactions. Additionally, IT has facilitated the rapid dissemination of information, making knowledge more accessible and democratizing education through online platforms and digital resources.In the realm of business, IT has revolutionized operational processesand decision-making strategies. Enterprise resource planning (ERP) systems, customer relationship management (CRM) software, and data analytics tools enable organizations to streamline operations, optimize resource allocation, and gain valuable insights into market trends and consumer behavior. Moreover, the integration of IT into supply chain management has enhanced logistics and distribution networks, facilitating efficient product delivery and inventory management.Healthcare is another sector that has witnessed tremendous advancements due to IT. Electronic health records (EHRs) have improved data management and patient care coordination, while telemedicine applications have expanded access to medical services, particularly in remote or underserved areas. Furthermore, advanced imaging technologies, robotic surgeries, and computational drug design have revolutionized diagnostic and therapeutic approaches, leading to improved patient outcomes and advancing medical research.Cybersecurity has emerged as a critical aspect of IT, as the increasing reliance on digital systems and the exchange of sensitive information has made data protection a paramount concern. IT professionals work diligently to develop robust security measures, such as firewalls, encryption techniques, and intrusion detection systems, to safeguard against cyber threats and ensure the confidentiality, integrity, andavailability of digital assets.Moreover, IT has played a pivotal role in advancing scientific research and innovation. High-performance computing (HPC) systems and sophisticated simulations have enabled scientists to tackle complex problems, analyze vast amounts of data, and model intricate phenomena across various disciplines, from astrophysics and climate research to drug discovery and materials science.As IT continues to evolve, emerging technologies such as artificial intelligence (AI), machine learning, and the Internet of Things (IoT) are poised to further transform our lives. AI algorithms are being integrated into numerous applications, from virtual assistants and predictive analytics to autonomous vehicles and intelligent decision support systems. IoT, on the other hand, is enabling the interconnectivity of physical devices and sensors, paving the way for smart homes, cities, and industrial automation.While the advancements in IT have brought about numerous benefits, they also raise ethical considerations and challenges. Issues related to privacy, data security, algorithmic bias, and the responsible development and deployment of AI systems require careful deliberation and proactive governance to ensure that technology serves the greater good of society.In conclusion, information technology has permeated virtually every aspect of our modern world, reshaping the way we live, work, and interact. As a dynamic and ever-evolving field, IT continues to push the boundaries of innovation, driving progress and shaping the future of our global society. Embracing the potential of IT while addressing its ethical implications will be crucial in navigating the technological landscape ahead.。
智慧病房系统英文缩写建设方案
Key
Technology
03 Implementatio n and
Difficulty
Breakthrough
Application of Internet of Things Technology
• Device Connection and Communication: Implement the connection and communication of medical devices, sensors, actuators, and other IoT devices to ensure the stability and real-time performance of data transmission.
Realize real-time monitoring and regulation of the ward environment, improve the living comfort and treatment effectiveness of patients.
Realize intelligent management of medical equipment, improve the utilization efficiency of medical resources and the work efficiency of medical staff.
• Promoting the development of smart healthcare: As an important component of smart healthcare, the construction of smart ward systems helps to promote the development of the entire smart healthcare field.
DSS4智能决策支持系统IDSSIntelligentDecision-科学网
8.1 决策支持系统（DSS）
系统结构
8.1 决策支持系统（DSS）
3 专家系统（ES，Expert System） 专家系统是以计算机为工具，利用专家知识及知识推理等技术来理解 与求解问题的知识系统。
特点：能进行某些通常由人来求解的工作；以规则或框架的形式表示 知识；可以和人进行相互对话；能同时考虑多个假设。
8.2 计算机集成制造/管理系统 （CIMS）
CIMS系统结构
8.2 计算机集成制造/管理系统 （CIMS）
CIMS的相关技术 CAD（Computer Aided Design，计算机辅助设计） /CAPP（Computer Aided Process Planning ，计算机辅助工艺规划） /CAM（Computer Aided Manufacturing ，计算机辅助制造） /CAE（Computer Aided Engineering ，计算机辅助工程分析）
第8章 管理信息系统的发展
• 主要内容
8.1 决策支持系统（DSS）
8.2 计算机集成制造/管理系统（CIMS） 8.3 电子商务（EC） 8.4 数据仓库 8.5 信息资源管理（IRM）
8.1 决策支持系统（DSS）
1． 决策
•决策是组织或个人为了将来达到某种目的而做出的一系列决定，是为 了解决某个问题，或实现某个预定目标而必须进行的某个重要活动。
8.1 决策支持系统（DSS）
2． 决策支持系统 决策支持系统（DSS， Decision Supporting System），是以管理科学、 运筹学、控制论和行为科学为基础，以计算机技术、仿真技术和信息技 术为手段，针对半结构化的决策问题，支持决策活动的具有智能作用的 人机系统。 主要特点 （1）系统的使用面向决策者，在运用DSS的过程中，参与者都是决策者。 （2）系统解决的问题是针对半结构化的决策问题，模型和方法的使用是 确定的，但是决策者对问题的理解存在差异，系统的使用有特定的环境， 问题的条件也不确定和唯一，这使得决策结果具有不确定性。 （3）系统强调的是支持的概念，帮助决策者作出科学的决策。 （4）系统的驱动力来自模型和用户，人是系统运行的发起者，模型是系 统完成各环节转换的核心。 （5）系统运行强调交互式的处理方式，一个问题的决策要经过反复的、 大量的、经常的人机对话，人的因素如偏好、主观判断、能力、经验、 价值观等对系统的决策结果有重要的影响。
基于改进BiLSTM-CRF模型的网络安全知识图谱构建
现代电子技术Modern Electronics TechniqueMar. 2024Vol. 47 No. 62024年3月15日第47卷第6期0 引 言随着互联网技术的发展，企业的网络资产比重逐渐增大。
根据2022年中国互联网发展报告[1]显示，来自网络空间的安全威胁愈发严重，经济财产损失风险逐年攀升。
前沿网络安全防控智能化技术更注重于从全维度、多视角的方面来感知网络空间威胁，而挖掘企业各类网络攻击的关联性、策略、后果等要素能够有效地提升企业对网络安全运维管理的效率[2]。
知识图谱（Knowledge Graph, KG ）通过在特定领域海量数据中抽取的知识构建领域知识图谱，数据规模、特殊语义关系使其实用性变得更强[3]。
目前，企业内的网络空间中所存在的威胁知识大部分没有形成很好的知识组织，在面向企业的网络安全运维的场景下，缺少能够有效涵盖网络空间威胁信息、反映企业网络安全态势以及支撑辅助安全决策的知识图谱；开源的漏洞信息库和威胁信息库等大多都是半结构化知识，而企业日常的网络安全运维数据中又包含大量的结构化和非结构化的报告，这些异构数据难以被企业直接利用来进行网络空间的防护。
知识图谱能够有效地整合这些存在潜在联系的网络安全运维相关知识，将离散的多源异构数据通过基于深度学习的信息提取模DOI ：10.16652/j.issn.1004‐373x.2024.06.003引用格式：黄智勇，余雅宁，林仁明，等.基于改进BiLSTM‐CRF 模型的网络安全知识图谱构建[J].现代电子技术，2024，47（6）：15‐21.基于改进BiLSTM⁃CRF 模型的网络安全知识图谱构建黄智勇1，2， 余雅宁1， 林仁明2， 黄 鑫1， 张凤荔1（1.电子科技大学 信息与软件工程学院， 四川 成都 610054； 2.四川省市场监督管理局数据应用中心， 四川 成都 610066）摘 要： 针对网络安全领域的图谱构建任务，基于BiLSTM‐CRF 模型引入了外部网络安全词典来加强网络安全文本的特征，并结合多头注意力机制提取多层特征，最终在网络安全数据集取得了更优异的结果。
人工智能背景下科技型企业智能财务决策应用问题研究
2020年软 件2020, V ol. 41, No. 5基金项目: 2019年度哈尔滨商业大学研究生科研创新项目课题：黑龙江省科技型企业智能财务决策案例研究(项目编号：YJSCX2019-589HSD)；2019年度黑龙江省会计学会会计科研立项课题“大数据、互联网、人工智能背景下财务理论的跨界融合与重构”(项目编号：20190015)作者简介: 王正博(1995–)，女，研究生，主要研究方向：财务管理；李静静(1994–)，女，研究生，主要研究方向：财务管理；李采玲(1995–)，女，研究生，主要研究方向：财务管理；高晗(1996–)，女，研究生，主要研究方向：财务管理；黄华(1996–)，女，研究生，主要研究方向：财务会计。
人工智能背景下科技型企业智能财务决策应用问题研究王正博1，李静静1，李采玲2，高 晗2，黄 华2（1. 哈尔滨商业大学 会计学院，黑龙江 哈尔滨 150028；2. 哈尔滨商业大学 会计学院，黑龙江 哈尔滨 150028）摘 要: 近年来，随着人工智能的发展日趋成熟，已对人们的生活产生了方方面面的影响，为人们的生产生活带来了便利性和简洁性，同时对财务决策方面的影响也日渐深入。
多年来国内外学者们对新背景下的财务决策进行了激烈的探讨，形成了丰富的研究成果，通过梳理文献资料发现，现有国内外研究成果多数仅针对传统财务决策模式创新进行研究，而对于人工智能背景下并未形成完善的财务决策框架。
因此本文以人工智能等手段为基本理论基础，分析财务决策四大活动在人工智能背景下产生的变化以及人工智能如何应用在具体财务决策过程中，并且应用渗透于科技型企业财务决策中进行实践探索，以适应时代发展的需要。
关键词: 人工智能；科技型企业；财务决策中图分类号: TP18 文献标识码: A DOI ：10.3969/j.issn.1003-6970.2020.05.012本文著录格式：王正博，李静静，李采玲，等. 人工智能背景下科技型企业智能财务决策应用问题研究[J]. 软件，2020，41（05）：61 65Research on the Application of Intelligent Financial Decision in Scientific andTechnological Enterprises Under the Background of Artificial IntelligenceWANG Zheng-bo 1, LI Jing-jing 1, LI Cai-ling 2, GAO Han 2, HUANG Hua 2(1. Accounting College of Harbin University of Commerce, Harbin 150028, China ; 2. Accounting College of Harbin University of Commerce, Harbin 150028, China )【Abstract 】: In recent years, with the development of artificial intelligence becoming more and more mature, it has had an impact on people's life in all aspects, brought convenience and simplicity to people's production and life, and also had an increasingly in-depth impact on financial decision-making. For many years, scholars at home and abroad have made a heated discussion on financial decision-making in the new context, and formed a wealth of research results. Through combing the literature, it is found that most of the existing research results at home and abroad only focus on the innovation of traditional financial decision-making mode, but not form a perfect financial deci-sion-making framework in the context of artificial intelligence. Therefore, based on the basic theory of artificial in-telligence, this paper analyzes the changes of the four major financial decision-making activities in the background of artificial intelligence and how to apply artificial intelligence in the specific financial decision-making process, and how to apply it to the financial decision-making of technology-based enterprises for practical exploration to meet the needs of the development of the times.【Key words 】: Artificial intelligence; Scientific and technological enterprise; Financial decision0 引言随着时代的发展进步，互联网、大数据、人工智能等智能化手段不断涌现，对会计领域产生的影响也是愈演愈烈。
智能优化极限学习机方法研究及在疾病诊断中的应用
—————————————————————智能优化极限学习机方法研究及在疾病诊断中的应用—————————————————————Research on Intelligent Optimization based-Extreme Learning Machine with Application to Disease Diagnosis————————————作者姓名：刘通专业名称：计算机系统结构指导教师：胡亮教授学位类别：工学博士论文答辩日期： 2020 年 11 月 29 日授予学位日期：年月日答辩委员会组成：姓名职称工作单位主席：吴国伟教授大连理工大学委员：郭立红研究员中国科学院长春光学精密机械与物理研究所刘淑芬教授吉林大学秦贵和教授吉林大学赵宏伟教授吉林大学未经本论文作者的书面授权，依法收存和保管本论文书面版本、电子版本的任何单位和个人，均不得对本论文的全部或部分内容进行任何形式的复制、修改、发行、出租、改编等有碍作者著作权的商业性使用（但纯学术性使用不在此限）。
否则，应承担侵权的法律责任。
答辩决议书论文题目:智能优化极限学习机方法研究及在疾病诊断中的应用作者姓名:刘通专业:计算机系统结构学院:计算机科学与技术学院答辩委员会姓名职称工作单位是否博导主席吴国伟教授大连理工大学是委员郭立红研究员中科院长春光学精密机械与物理研究所是赵宏伟教授吉林大学是刘淑芬教授吉林大学是秦贵和教授吉林大学是答辩委员会对论文及答辩情况的评语:刘通同学在攻读博士学位期间对于极限学习机和核极限学习机等机器学习方法进行研究，构建疾病诊断模型，主要工作包括：(1) 建立一种基于分散觅食正余弦优化算法的极限学习机模型（DFSSCA-ELM）对红斑鳞状皮肤疾病进行诊断，有效提高模型预测能力。
(2)提出一种改进的极限学习机模型（CDESSA-ELM）来对胸腔积液进行诊断。
采用混沌初始机制和差分进化机制提高模型的预测能力。
(3)建立一种基于精英混沌黏菌算法的核极限学习机模型（ECSMA-KELM）对肾结石疾病进行诊断。
高中英语写智能机器人的作文
高中英语写智能机器人的作文In today's rapidly evolving technological landscape, the emergence of intelligent machines, commonly known as robots, has captivated the imagination of people across the globe. As a high school student, I am particularly intrigued by the potential of these advanced systems and their impact on our lives.Robots have become an integral part of our modern world, revolutionizing various industries and transforming the way we live. From factory automation to healthcare, these intelligent machines have demonstrated their ability to perform tasks with remarkable precision, speed, and efficiency. As I delve deeper into the world of robotics, I am amazed by the sheer ingenuity and creativity that goes into their design and development.One of the most fascinating aspects of intelligent robots is their capacity for autonomous decision-making. Unlike traditional machines that rely on pre-programmed instructions, these advanced systems are equipped with sophisticated algorithms and machine learning capabilities that allow them to adapt to changing environments and make informed choices on their own. This autonomy has opened up a wide range of possibilities, from self-driving cars that can navigate complex traffic scenarios to surgical robots that can perform delicate medical procedures with unparalleled precision.As I contemplate the future of robotics, I am particularly intrigued by the potential for these systems to revolutionize the field of healthcare. Imagine a world where robotic assistants could provide personalized care and support to the elderly or individuals with disabilities, helping them maintain their independence and improve their quality of life. These intelligent machines could also be deployed in emergency situations, delivering life-saving medical aid in remote or hazardous areas where human access is limited.Moreover, the integration of artificial intelligence (AI) with robotic systems has led to the development of truly remarkable capabilities. AI-powered robots can now engage in natural language processing, allowing them to communicate with humans in a more intuitive and natural way. This opens up a world of possibilities for human-robot interaction, where we can collaborate with these intelligent machines to tackle complex problems and achieve unprecedented levels of productivity and efficiency.However, the rise of intelligent robots also raises important ethical and societal considerations that we must address. As these systems become more advanced and autonomous, there are valid concernsabout the impact on employment, as certain tasks and jobs may become automated. It is crucial that we develop robust policies and regulations to ensure that the benefits of robotics are equitably distributed and that the transition to an increasingly automated workforce is managed responsibly.Additionally, the issue of privacy and data security in the context of intelligent robots is a growing concern. As these systems become more interconnected and reliant on vast amounts of data, we must ensure that robust safeguards are in place to protect sensitive information and prevent the misuse of this technology.Despite these challenges, I believe that the potential benefits of intelligent robots far outweigh the risks. These advanced systems have the power to enhance our lives in countless ways, from improving healthcare outcomes to enhancing our overall quality of life. As a high school student, I am excited to witness the continued evolution of robotics and to play a role in shaping its future.As I look ahead, I am confident that the continued advancement of intelligent robots will lead to groundbreaking discoveries and solutions that will positively impact our world. Whether it is in the realm of scientific research, environmental conservation, or even space exploration, these remarkable machines have the potential to push the boundaries of what is possible and to help us overcomesome of the most pressing challenges facing humanity.In conclusion, the rise of intelligent robots is a testament to the incredible ingenuity and creativity of the human mind. As we continue to push the boundaries of technology, it is crucial that we do so in a responsible and ethical manner, ensuring that the benefits of these advanced systems are shared equitably and that we address the societal implications with great care and foresight. As a high school student, I am eager to be a part of this exciting journey and to contribute to the ongoing evolution of intelligent robotics.。
管理科学与工程 硕士 数据挖掘与商务智能 研究方向
管理科学与工程硕士数据挖掘与商务智能研究方向Research Interest in Data Mining and Business Intelligence for Masters in Management Science and EngineeringData mining and business intelligence have become crucial fields in the modern business landscape. As vast amounts of data are generated every day, organizations need professionals who can extract valuable insights from this data to make informed decisions. With an increasing demand for skilled individuals in this field, pursuing a research direction focused on data mining and business intelligence within the management science and engineering discipline can open up numerous opportunities.Data mining involves the process of discovering patterns, correlations, and trends within large datasets. Through advanced statistical techniques, machine learning algorithms, and artificial intelligence tools, data scientists can identify hidden patterns that can drive decision-making processes. In a business context, thismeans uncovering critical insights about customer behavior, market trends, and operational efficiency.The research direction of data mining within the management science and engineering field allows you to explore various subfields such as predictive analytics, text mining, social network analysis, and spatial-temporal data mining. By delving into these areas, you can gain a comprehensive understanding of how different methodologies are applied to solve real-world problems.Business intelligence complements data mining by focusingon transforming raw information into actionable insights.It involves the collection, integration, analysis, interpretation, and presentation of data to support managerial decision-making at all levels of an organization. As a researcher in this field of study, you will be equipped with the knowledge to develop effective strategies for extracting value from data assets.Your research could involve exploring topics such as data visualization techniques for presenting complex informationin a user-friendly manner or designing intelligent decision support systems that assist managers in making strategic choices based on accurate analyses of available information.By integrating both data mining and business intelligence concepts into your studies within the management scienceand engineering field specifically targeted towards commercial applications (i.e., marketing analytics orsupply chain optimization), you will be well-equipped with skills that are highly sought after by businesses across industries.Overall, specializing in the research direction of data mining and business intelligence within the management science and engineering discipline can lead to exciting opportunities. With the right expertise, you can contribute to solving real-world challenges faced by organizationswhile also making a significant impact on their overall success.在当今的商业环境中，数据挖掘和商务智能已成为至关重要的领域。
高等教育领域中的ChatGPT与教师智能化辅助决策协作模式研究(英文中文双语版优质文档)
高等教育领域中的ChatGPT与教师智能化辅助决策协作模式研究（英文中文双语版优质文档）Research on the Collaborative Model of ChatGPT and Teachers' Intelligent Assisted Decision-Making in the Field of Higher Education (English and Chinese bilingual version of high-quality documents)Research on the Collaborative Mode of ChatGPT and Teachers' Intelligent Assisted Decision-Making in the Field of Higher EducationIn recent years, the application of artificial intelligence technology in the field of education has been increasing, among which the intelligent assistance system based on ChatGPT provides new possibilities for teachers' decision-making. This article will discuss the research and application of ChatGPT and teachers' intelligent assisted decision-making cooperation model in the field of higher education from multiple perspectives.First, ChatGPT, as an intelligent dialogue model, can provide support for information retrieval and knowledge recommendation for teachers. Teachers need to obtain relevant educational resources and academic knowledge in the decision-making process, and ChatGPT can interact with teachers through natural language, and provide accurate and real-time information retrieval and knowledge recommendation services according to teachers' queries and needs. In this way, teachers can obtain the information they need faster to provide strong support for decision-making.Secondly, ChatGPT can also be used as a teacher's intelligent assistant to assist teachers in completing tedious teaching tasks and decision-making processes. For example, in terms of student evaluation and feedback, ChatGPT can help teachers analyze and summarize students' evaluation opinions, extract key information, and help teachers understand students' learning needs and problems. In addition, in terms of personalized recommendation of teaching resources and student emotional analysis, ChatGPT can also provide teachers with decision-making information and suggestions to help teachers better understand students' learning status and emotional needs.However, the cooperation mode between ChatGPT and teachers' intelligent assisted decision-making still faces some challenges. First of all, ChatGPT has limitations in understanding and expression during the dialogue process. Although ChatGPT has achieved remarkable progress in natural language processing, it still suffers from comprehension difficulties and ambiguous answers to complex questions. Therefore, teachers need to understand the limitations of ChatGPT and provide effective guidance and interpretation during use.Second, with the widespread application of ChatGPT in education, privacy and ethical issues have also attracted much attention. ChatGPT obtains information through dialogue with users, so it involves issues of personal privacy and data security. Educational institutions and developers need to take appropriate privacy protection measures to ensure that student and teacher information is not misused or leaked.In addition, as a technical tool, ChatGPT still requires teachers' professional knowledge and experience for effective decision-making guidance and interpretation. Teachers should be aware of the auxiliary role of ChatGPT and use it as a tool to assist decision-making, rather than replace the role of teachers. Teachers' professional knowledge and experience are crucial to the trade-offs and judgments of decision-making, and cannot be completely relied on machine intelligence.To sum up, the collaborative mode of ChatGPT and teachers' intelligent assisted decision-making has broad application prospects in the field of higher education. By collaborating with ChatGPT, teachers can obtain required information faster, complete tedious teaching tasks, and obtain more accurate and personalized decision support from them. However, teachers need to understand the limitations of ChatGPT, apply its auxiliary functions reasonably, and pay attention to the protection of privacy and ethical issues. In future research and practice, we should continue to explore the best practice of ChatGPT and teachers' intelligent assisted decision-making cooperation model, so as to continuously improve teachers' teaching quality and decision-making effects.高等教育领域中的ChatGPT与教师智能化辅助决策协作模式研究近年来，人工智能技术在教育领域的应用日益增多，其中基于ChatGPT的智能辅助系统为教师的决策提供了新的可能性。
信息管理与智能决策的研究计划
信息管理与智能决策的研究计划Research Plan on Information Management and IntelligentDecision-MakingAs the world becomes increasingly interconnected and data-driven, the field of information management and intelligent decision-making has emerged as a crucial aspect of modern society. This research plan aims to explore the intersection of these two domains, with a focus on leveraging advanced technologies to enhancedecision-making processes.随着世界日益互联和数据驱动，信息管理与智能决策已成为现代社会至关重要的领域。
本研究计划旨在探索这两个领域的交叉点，重点利用先进技术来优化决策过程。
Firstly, we will delve into the core principles of information management, encompassing the effective collection, organization, storage, retrieval, and utilization of data. This involves the study of various techniques and tools that facilitate the management of vast amounts of information, enabling organizations to make informed decisions based on accurate and timely data.首先，我们将深入研究信息管理的核心原则，包括数据的有效收集、组织、存储、检索和利用。
智能制造英文版
智能制造英文版Intelligent manufacturingAn overviewIntelligent manufacturing deep in artificial intelligence research.Generally think that intelligence is the sum of knowledge and intelligence,the former is the basis of intelligence,the latter is the ability to acquire and apply knowledge to solve.Intelligent manufacturing should contain intelligent manufacturing technology and intelligent manufacturing system.The intelligence technique of manufacture is refers using the computer simulation marks intelligent activities such as expert’s analysis,judgment,inference, idea and decision-making and so on,and fuses organically these intelligent activity and the intelligent machine,applies its penetration in entire manufacture enterprise’s each subsystem(e.g. management decision-making,purchase, product design,productive plan,manufacture, assembly,quality assurance and market sale and so on).Realizes the entire manufacture enterprise to manage the operation highlyflexibility and integration,thus substitutes or extends in the manufacture environment expert’s partial mental labor, and carries on the collection,the memory,the consummation,sharing,the inheritance and the development of the manufacturing industry expert’s intelligent information,enhances the production efficiency enormously and the advanced technique of manufacture.The intelligent manufacture system is refers based on IMT(intelligent manufacturing technology),by the computer synthesis application artificial intelligence technology(e.g.artificial neural networks,genetic algorithm and so on), the intelligence manufacture machine,the agent technology,the parallel projects,the life sciences and the systems engineering theory and the method,in the international standardization and interchangeable foundation,causes the entire enterprise to make each subsystem to intellectualize separately,and causes the manufacture system to form by the network integrates,the highautomated one king of manufacture system.Intelligent manufacturing system can not only in practice constantly enrich the knowledge base,have the function of self-learning,and collecting and understanding of environmental information and its information,analysis and judgment and the ability to plan their actions.The basic principleStarting from the essential feature of intelligent manufacturing system in distributed manufacturing network environment,according to the basic idea of distributed integration,In the application of distributed artificial intelligence theory and method of multi Agent system, realize flexible manufacturing unit of the intelligent and flexible manufacturing system based on network intelligent integration.According to the characteristics of the distribution system of isomorphism in a local area forms for realizing intelligent manufacturing system based on the actual also reflects theinternet-based global manufacturing the realization of the intelligent manufacturing system model under the network environment.The overall idea of distributed IMS network:IMS is the essential characteristics of the individual manufacturing unit of "autonomy"and the system as a whole "self-organizing ability",its basic pattern is distributed more intelligent system.Based on this understanding,and considering the internet-based global manufacturing network environment,we put forward the Agent based distributed IMS network's basic idea,as shown in figure 1.On the one hand,through the Agent give autonomy to each manufacturing unit,making it a fully functional,autonomy, an independent entity;On the other hand, through the coordination and cooperation between the Agent,gives system self-organization ability.Multi Agent system implementation pattern of the system is easy to design, implementation and maintenance,reduce thecomplexity of the system,enhance the system's restructuring,scalability and reliability,and improve the flexibility, adaptability and agility of the system.Based on the above framework,combined with the CNC machining system,development and application of distributed network prototype system by system manager,mission planning,design and producers of four nodes.Systems manager node including two database server,database server and Agent system is responsible for the management of the entire global database,available for access of nodes in the prototype system for data query,read,storage and retrieval operations,and for each node for data exchange and sharing,to provide a public system,the Agent is responsible for the system in the network and the external interaction,through the Web server on the Internet home page of the system,users can access online home page the information related to obtaining the system,and according to their own needs,to decidewhether the system is to meet these requirements,the system of the Agent is also responsible for monitoring the interactions between the various nodes on prototype system, such as record and real-time display of sending and receiving messages between nodes, task execution,etc.Mission planning nodes by the task manager and its Agent(task manager Agent), its main function is to task planning,from the Internet is decomposed into several subtasks,and then through the way of bidding, bidding to the task allocation of each node.Design node by CAD tools and its proxy Agent(design),it provides a good man-machine interface so that designers can effectively and computer interaction,common to complete the design task.CAD tools to help design personnel according to user requirements for product design;Designed the Agent is responsible for online registration, cancellation registration,database management,interaction with other nodes, decide whether to accept the design task andsubmit a task to task the sender.Producers node is actually the project research and development of an intelligent manufacturing system(intelligent manufacturing unit),including processing center and its network proxy Agent(machine). The intelligent adaptive machining center configuration.The CNC system is controlled by intelligent controller processing process, to give full play to the processing of automated processing equipment potential, improve processing efficiency;Have certain ability of self diagnose and self repair,in order to improve the processing the reliability and safety of the equipment operation;Have the ability to interact with the external environment;With open architecture to support the system integration and extension.The prototype system work:Every node in the system must be registered through the network,to become the formal member of the prototype system to obtain the corresponding privileges,to collaboratewith other nodes in the system,common to complete the system task.The whole process of operation of the prototype system is as follows:(1)any network user can access the prototype system of the home page for information about the system,but also through the fill out and submit user order form provided by the system home page issued orders to the system;(2)if received and accept the network user's orders,Agent system is to be deposited in the global database,from the global database,mission planning nodes can take out the order,mission planning,the task decomposition into several subtasks,and assign these subtasks prototype system access nodes;(3)product design subtasks are assigned to design node,the node through good human-computer interaction to complete product design sub-tasks,generate the corresponding CAD/CAPP data and documents, and nc code,and these data and documents in the global database,finally submit the subtasks to mission planning nodes;(4) processing subtasks are assigned to producers,once the subtasks was accepted by the producers nodes,machine Agent will be allowed to read the necessary data from the global database,and to transfer the data to the processing center,processing center, according to these data and command to finish processing the subtasks,and the running status information transmitted to the machine Agent,machine Agent returns the result to the mission planning nodes,submit the subtask;(5)in the system during the running of the whole,the Agent is the interaction between the various nodes in the system for recording, such as message sending and receiving,a global database data read and write,query the node name,type,address,ability,and task completion,etc.(6)Network client can understand order execution and results.The developmentIntelligent manufacturing deep in artificial intelligence research.Artificial intelligence is the intelligence of implementation of using artificial method onthe computer.Of complicated as the WanShanHua and the structure of the product performance and refinement,as well as the function of diversification,prompting a surge in product design information and process information contained,with internal information flow increase of production line and production equipment,manufacturing process and management information must also soared,a hotspot and frontier,and thus prompt the development of manufacturing technology to improve manufacturing system for the explosive growth of manufacturing information processing ability,efficiency and scale.At present,the advanced manufacture equipment left the information input cannot operate,flexible manufacturing system(FMS)once they are cut off the source of information will immediately cease to work. Expert thinks,the manufacturing system is driven by the original energy into information driven,this requires a flexible manufacturing system requires not only,but also show that the intelligent,otherwise itis difficult to deal with such a large amount of workload and complex information.Secondly, the complex environment of rapidly changing market demand and fierce competition,also called for the manufacturing system showed higher flexibility,agility and intelligence. Across the world,although the overall intelligent manufacturing was still in the stage of conceptual and experimental,but governments are included in the national development plans,this push to implement.In 1992the implementation of new technology policy and support by the President said the key to the important technical(Critical Techniloty),including information technology and new manufacturing technology, ease of intelligent manufacturing technology, the ernment hopes the move to transform traditional industry and start a new industry.Canada's1994~1998development strategy plan,think the future knowledge intensive industry is driving the global economy and Canada,the basis of economic developmentthought is very important to development and application of intelligent system,and put the specific research project selection for intelligent computer,man-machine interface, mechanical sensor,the robot control system integration,the new device,the dynamic environment.Japan's in1989,intelligent manufacturing system is proposed and launched in1994,the advanced manufacturing international cooperation research projects, including the companies to integrate and global manufacturing,manufacturing knowledge system,distributed intelligent control system,rapid product realization of distributed intelligent system technology, etc.Research of information technology in the European Union ESPRIT project,the project is funded by the market potential of information technology.1994and the start of the new R&D project,select the39core technologies,of which three(information technology, molecular biology and advanced manufacturingtechnology)are highlights the intelligent manufacturing location.China at the end of the80's will "intelligent simulation"the main issue in the national science and technology development planning,understanding has made a number of achievements in the expert system, pattern recognition,robotics,Chinese machine.Recently,the State Ministry of science and technology put forward formally "industrial intelligent engineering",as an important part of the innovation ability of technology innovation project construction, intelligent manufacturing will be an important content of the project.Thus,the intelligent manufacturing is arising in the world,it is the development of manufacturing technology,especially the inevitable manufacturing development of information technology,is the result of the development of automation and integration technology in depth.Integrated featuresWith the traditional manufacture systemcompares,IMS has following several characteristics:(1)From organization abilityIn the IMS,each kind of composition unit can according to the work duty need, voluntarily build up one kind of ultra flexible best structure,and defers to the most superior way movement.Not only its flexibility displays in the movement way,but also displays in the structural style.After completing the task,this structure dismisses voluntarily,prepares in the next duty builds up a new kind of structure.The voluntarily organization ability is an IMS important symbol.(2)Autonomy abilityIMS has the abilities such as collection and the understanding the environmental information and own information,and carries on the analysis to judge and to plan own behavior ability.The powerful knowledge library and based on the knowledge model is the autonomy ability foundation.IMS can act according to the environment and own workcondition information to carries on the monitor and processing,and according to the processing finally self-adjusting control strategy,uses the best movement plan.This kind of autonomy ability causes the entire manufacture system to have the anti jamming, auto-adapted and fault-tolerant and so on.(3)The ability of self-study and maintenanceIMS can take the original expert knowledge as the foundation,in reality carries on the study unceasingly,the perfect system knowledge library,and deletes the unsuitable knowledge in the storehouse, causes the knowledge library to hasten reasonably.At the same time,it also can carry on the self-diagnosis,the elimination and repairing to the system failure.The kind of character enables IMS to optimize and to adapt to each kind of complex circumstances.(4)Entire manufacture system intelligent integrationWhile IMS emphasized each subsystem intellectualization,pays great attention to the entire manufacture system the intelligentintegration.This is the basic difference between IMS and“the intellectualized isolated”which specially applied in the manufacture process.IMS contains each subsystem,and integrates them in a whole, realizes the whole intellectualization. (5)Man-machine integration intelligence systemIMS is not a pure the artificial intelligence the system,but is the man-machine integration intelligence system, is one kind of mix intelligence.On the one hand,the man-machine integration prominent person’s core status in manufacture system, simultaneously under the intelligent machine coordination,well has displayed human’s potential,causes between the man-machine to display one kind of equality to work together as colleagues,“understands”mutually, cooperates mutually relations,causes them to reveal respectively in the different level, complements each other.Therefore,in IMS, the high quality,the high intelligent person will play a better role,the machineintelligence and human’s wisdom integration of machinery Mechatronics issue can integrate truly in together.In summary,we may view IMS as one kind of pattern,it is the collection of automation, flexibility,integration and intellectualization in a body,and unceasingly to depth development advanced manufacture system.(6)Virtual realityThis technology supports the realization hypothesized manufacture,also realizes one of high level man-machine integration.The man-machine union is a new generation of intelligent contact surface,causes the available hypothesized method with intelligent performance into reality,it is a dominant character of intelligent manufacture.Future development1、Artificial intelligence technology.Since the goal of IMS is computer simulation of intelligence activities of manufacturing human experts,partial mentallabor to replace or extension of the people, so the artificial intelligence technology has become one of the key technology of IMS.IMS and artificial intelligence technology (expert system,artificial neural network, fuzzy logic)is closely related to.2、Concurrent engineering.In view of the manufacturing,concurrent engineering is an important technical method, used in IMS,will reduce the repetition blindness and the design of the product design.3、Information network technology.Information network technology is the process of manufacturing system and each link "intelligent"support.The information network is also the manufacturing information and knowledge flow channel.4、The virtual manufacturing technology.Virtual manufacturing technology can simulate the entire life cycle of product in the product design stage,thus the more effective,more economical,more flexible organization of production,the productdevelopment cycle is short,the product cost is the lowest,the optimal product quality, production efficiency is the highest assurance.At the same time,the virtual manufacturing technology is the prerequisite for the engineering realization of parallel.5、Discipline construction.Collect and understand the environment information and its information and analysis judgment and plan their behavior.Strong knowledge base and knowledge based model is the basis of self-discipline.6、Man-machine integration.Intelligent manufacturing system is not only the"artificial intelligence system,and human-machine intelligent system,is a kind of hybrid intelligent.Want to completely replace human intelligence artificial intelligence expert in manufacturing process, analysis,judgement,decision independently undertake the task,at present is not realistic.Humachine highlighted the core position in manufacturing system,combined with intelligent machines,better play ofhuman potential,to achieve a kind of collaborative working relationship of equality,so that the two made at different levels,each other.7、Self organization and super flexible.To each unit in intelligent manufacturing systems can be based on task,form an optimal structure,the flexible displays not only operation mode,but also in the structure form, so that the flexible super flexible,similar to biological features,overall as a group of human experts.Conclusion:nowadays,the research of intelligent manufacturing at home and abroad was still in the stage of concept formation and experimental exploration.In recent years, developed for the specific link,the specific problems in the process of manufacturing the "intelligent island",and"smart"machine for manufacturing environment full of research is still in its beginning stage.Intelligent manufacturing is a rich content,wide prospect area.In the era of socialinformatization,the new century of knowledge economization,vigorously carry out the research of intelligent manufacturing technology and system,will improve the overall level of manufacturing industry inthe comprehensive our country,enhancenational strength.。
openai-translator gpt译名表
Openai-Translator Gpt译名表以下是OpenAI-Translator 中文到英文的GPT 译名表：人工智能-> Artificial intelligence自然语言处理-> Natural language processing机器学习-> Machine learning深度学习-> Deep learning语音识别-> Speech recognition图像识别-> Image recognition智能助手-> Smart assistants智能家居-> Smart homes自动驾驶-> Autonomous driving智能机器人-> Intelligent robots智能客服-> Smart customer service智能物流-> Smart logistics智能安防-> Smart security智慧医疗-> Smart healthcare智慧金融-> Smart finance智慧教育-> Smart education智慧农业-> Smart agriculture智慧城市-> Smart cities智慧零售-> Smart retailing智慧工业-> Smart industry智慧供应链-> Smart supply chain智慧交通-> Smart transportation智慧能源-> Smart energy智慧通信-> Smart communication智慧媒体-> Smart media智慧旅游-> Smart tourism智慧环保-> Smart environmental protection 智慧建筑-> Smart architecture智慧海洋-> Smart ocean智慧气象-> Smart meteorology智慧地球-> Smart planet智能制造-> Intelligent manufacturing智能芯片-> Intelligent chips智能传感器-> Intelligent sensors智能硬件-> Intelligent hardware智能软件-> Intelligent software智能网络-> Intelligent networks智能云服务-> Intelligent cloud services智能语音技术-> Intelligent voice technology 智能图像技术-> Intelligent image technology 智能数据分析-> Intelligent data analysis智能决策支持系统-> Intelligent decision support systems智能预测模型-> Intelligent predictive models智能推荐系统-> Intelligent recommendation systems智能交互界面-> Intelligent interactive interfaces智能安全防护-> Intelligent security protection智能远程监控-> Intelligent remote monitoring智能健康管理-> Intelligent health management智能交通管理-> Intelligent traffic management智能资产管理-> Intelligent asset management智能供应链管理-> Intelligent supply chain management智能客户服务-> Intelligent customer service智能人力资源管理-> Intelligent human resource management智能业务流程管理-> Intelligent business process management智能项目管理-> Intelligent project management智能财务管理-> Intelligent financial management智能市场营销管理-> Intelligent marketing management智能风险管理-> Intelligent risk management智能决策分析-> Intelligent decision analysis人工智能伦理问题研究-> Research on ethical issues of artificial intelligence人工智能法律法规研究-> Research on laws and regulations of artificial intelligence人工智能发展史研究-> Research on the history of artificial intelligence development人工智能产业研究-> Research on the artificial intelligence industry人工智能未来展望研究-> Research on the future development of artificial intelligence。