外文翻译：用层次分析法选择适当的项目交付方式

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层次分析法模型外文文献翻译2014年译文2000字

层次分析法模型外文文献翻译2014年译文2000字XXX (AHP) XXX。

the XXX whether the rity vector of alternatives remains the same or different when the XXX on the AHP process。

subjectivity。

and pair-XXX n。

2.XXXXXX fields。

including business。

engineering。

XXX smaller。

XXX。

3.MethodologyThe study used a case study XXX to test whether the rity vector of alternatives remains the same or different when the XXX individuals。

4.ResultsThe study found that the AHP methodology is effective in providing second XXX。

The rity vector of alternatives remained the same in most cases。

indicating that the AHP XXX。

therewere some cases where the rity vector of alternatives differed。

suggesting that the AHP methodology is not XXX。

5.nThe results of the study suggest that the AHP methodologycan be an effective tool for improving n-making quality。

However。

it is XXX。

物流治理外文文献外文翻译英文文献逆向物流运作渠道的决策方式

外文出处：Senthil, S., Srirangacharyulu, B., & Ramesh, A. (2021). A decision making methodology for the selection of reverse logistics operating channels. Procedia Engineering, 38, 4, 418–428.附件1：外文资料翻译译文逆向物流运作渠道的决策方式摘要：产品退货的有效治理是一项战略性的问题。

现在，客户希望厂商能够进展逆向物流系统，为了是返还的产品能够被回收。

随着逆向物流实践的不断进展和进步，逆向物流渠道的选择就显得愈来愈重要。

此刻有三种大体的逆向物流运作渠道：制造商自营，第三方运营和联合运营模式。

本文基于层次分析法（AHP）和技术模糊环境下逼近理想解排序法（TOPSIS）相结合的混合方式，提出了逆向物流运作渠道的选择和评判。

本文利用一个算例验证了该方式。

这种方式帮忙决策者更有效的选择能够知足客户要求的最正确渠道。

关键字：逆向物流多目标决策层次分析法1 引言由于有关环境的法律不断的出台，逆向物流慢慢引发了企业的关注。

逆向物流（RL）是一个计划、实施和操纵原材料能够高效、低本钱的流动的进程，也是为了达到取得更多的价值，关于在制品库存、产成品和相关的从消费者手中回到原生产商的信息进行适当的处置。

关于逆向物流的研究仍然处于探讨时期。

逆向物流使得企业降低本钱成为可能。

逆向物流概念了供给链被设计为有效的治理产品和零部件的流动，使得它们能够进行再制造、循环利用和流程的改良，以便加倍有效的利用这些资源。

逆向物流活动的执行包括各类功能部份：产品质量的把关，紧缩配置循环周期，产品的再制造与翻新，资产回收，谈判，外包和客户效劳。

除产品的存储和运输，增值效劳的价值如：JIT，快速反映和问题方案的解决也都是逆向物流的重要组成部份。

关于有缺点的产品进行再制造，维修和回收能够制造庞大利润的商业机遇。

层次分析法---文献翻译

层次分析法---文献翻译888大学毕业设计(论文)文献翻译题目层次分析法院、系(部) 计算机科学与技术学院专业及班级计科0903班姓名 888 指导教师 888 日期 2013年3月Analytic Hierarchy ProcessThe Analytic Hierarchy Process (AHP) is a structured technique for helpingpeople deal with complex decisions. Rather than prescribing a "correct" decision, the AHP helps people to determine one that suits their needs and wants. Based on mathematics and psychology, it was developed by Thomas L. Saaty in the 1970s and has been extensively studied and refined since then. The AHP provides a comprehensive and rational framework for structuring a problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. It is used throughout the world in a wide variety of decision situations, in fields such as government, business, industry, healthcare, and education.Several firms supply computer software to assist in using the process.Users of the AHP first decompose their decision problem into a hierarchy of more easily comprehended sub-problems, each of which can be analyzed independently. The elements of the hierarchy can relate to anyaspect of the decision problem—tangible or intangible, carefully measured or roughly estimated, well- or poorly-understood—anything at all that applies to the decision at hand.Once the hierarchy is built, the decision makers systematically evaluate its various elements, comparing them to one another in pairs. In making the comparisons, the decision makers can use concrete data about the elements, or they can use their judgments about the elements' relative meaning and importance. It is the essence of the AHP that human judgments, and not just the underlying information, can be used in performing the evaluations.The AHP converts these evaluations to numerical values that can be processed and compared over the entire range of the problem. A numerical weight or priority is derived for each element of the hierarchy, allowing diverse and often incommensurable elements to be compared to one another in a rational and consistent way. This capability distinguishes the AHP from other decision making techniques.In the final step of the process, numerical priorities are derivedfor each of the decision alternatives. Since these numbers represent the alternatives' relative ability to achieve the decision goal, they allow a straightforward consideration of the various courses of action.Uses and applicationsWhile it can be used by individuals working on straightforward decisions, Analytic Hierarchy Process (AHP) is most useful where teamsof people are working on complex problems, especially those with high stakes, involving human perceptionsand judgments, whose resolutions have long-term repercussions. Ithas unique advantages where important elements of the decision are difficult to quantify or compare, or where communication among team members is impeded by their different specializations, terminologies, or perspectives.Decision situations to which the AHP can be applied include:, Choice - The selection of one alternative from a given set of alternatives,usually where there are multiple decision criteria involved., Ranking - Putting a set of alternatives in order from most toleastdesirable Prioritization - Determining the relative merit of a setofalternatives, as opposed to selecting a single one or merely ranking them, Resource allocation - Apportioning resources among a set of alternatives, Benchmarking - Comparing the processes in one's own organization withthose of other best-of-breed organizations, Qualitymanagement - Dealing with the multidimensional aspects of quality and quality improvementThe applications of AHP to complex decision situations have numbered in the thousands, and have produced extensive results in problems involving planning, Resource allocation, priority setting, and selection among alternatives. Other areas have included forecasting, toreotal quality management, business process re-engineering ,quality function deployment， and the Balanced Scorecard.ManyAHP applications are never reported to the world at large, because they take place at high levels of large organizations where security and privacy considerations prohibit their disclosure. But some uses of AHP are discussed in the literature. Recently thesehave included:, Deciding how best to reduce the impact of global climate change (Fondazione Eni Enrico Mattei), Quantifying the overall quality of software system(Microsoftcorporation), Selecting university faculty(Bloomsburg University of Pennsy), Deciding where to locate offshore manufacturing plants(University ofCambridge), Assessing risk in operating cross-country prtroleumpipelines(AmericanSociety of Civil Engineers), Deciding how best to manage U.S. watersheds(U.S. Department of Agriculture)AHP is sometimes used in designing highly specific procedures for particular situations, such as the rating of buildings by historic significance. It was recently applied to a project that uses video footage to assess the condition of highways inVirginia. Highway engineers first used it to determine the optimum scope of the project, then to justify its budget to lawmakers.AHP is widely used in countries around the world. At a recent international conference on AHP, over 90 papers were presented from 19 countries, including the U.S., Germany, Japan, Chile , Malaysia, andNepal. Topics covered ranged from Establishing Payment Standards for Surgical Specialists, to Strategic TechnologyRoadmapping, to Infrastructure Reconstruction in Devastated Countries. AHP wasintroduced in China in 1982, and its use in that country has expanded greatly since then—its methods are highly compatible with the traditional Chinese decision making framework, and it has been used for many decisions in the fieldsofeconomics,energy,management,environment,traffic,agriculture, industry, and the military.Though using AHP requires no specialized academic trainning, the subject is widely taught at the university level—one AHP software provider lists over a hundredcolleges and universities among its clients. AHP is considered an important subject in many institutions of higher learning, includingschools of engineering and Graduate school of Business . AHP is also an important subject in the quality field, and is taught in many specialized courses including Six Sigma, Lean Six Sigma, and QFD.In China, nearly a hundred schools offer courses in AHP, and many doctoral students choose AHP as the subject of their research and dissertations. Over 900 papers have been published on the subject inthat country, and there is at least one Chinese scholarly journal devoted exclusively to AHP.ImplementationAs can be seen in the examples that follow, using the AHP involves the mathematical synthesis of numerous judgments about the decision problem at hand. It is not uncommon for these judgments to number in the dozens or even the hundreds. While the math can be done by hand or with a calculator, it is far more common to use one of several computerized methods for entering and synthesizing the judgments. The simplest of these involve standard spreadsheet software, while the most complex use custom software, often augmented by special devices for acquiring the judgmentsof decision makers gathered in a meeting room.Steps in using the processThe procedure for using the AHP can be summarized as:1. Model the problem as a hierarchy containing the decision goal,the alternativesfor reaching it, and the criteria for evaluating the alternatives.2. Establish priorities among the elements of the hierarchy bymaking a series ofjudgments based on pairwise comparisons of the elements. For example, whencomparing potential real-estate purchases, the investors might say they preferlocation over price and price over timing.3. Synthesize these judgments to yield a set of overall prioritiesfor the hierarchy.This would combine the investors' judgments about location, priceand timingfor properties A, B, C, and D into overall priorities for each property.4. Check the consistency of the judgments.5. Come to a final decision based on the results of this process.CriticismsThe AHP is now included in most operations research and management science textbooks, and is taught in numerous universities; it is used extensively in organizations that have carefully investigated its theoretical underpinnings. While the general consensus is that it isboth technically valid and practically useful, the method does have its critics.In the early 1990s a series of debates between critics andproponents of AHP was published in Management Science and The Journal of the Operational ResearchSociety. These debates seem to have been settled in favor of AHP.Occasional criticisms still appear. A 1997 paper examined possible flaws in the verbal (vs. numerical) scale often used in AHP pairwise comparisons. Another from the same year claimed that innocuous changesto the AHP model can introduce order where no order exists. A 2006 paper found that the addition of criteria for which all alternatives perform equally can alter the priorities of alternatives. An in-depth paper discussing the academic criticisms of AHP was published in Operations Research in2001.Most of the criticisms involve a phenomenon called rank reversal, discussed inthe following section.Rank reversalMany people hear about rank reversal and assume that there is some sort of proven principle about it that needs to be upheld in making decisions. That assumption has led to much misunderstanding of AHP and other decision making techniques. In actuality, rank reversal is a complex matter about which there are many conflicting ideas and opinions. This section offers a simplified explanation of the situation.Decision making involves ranking alternatives in terms of criteriaor attributes of those alternatives. It is an axiom of some decision theories that when new alternatives are added to a decision problem, the ranking of the old alternatives must not change. But in the real world, adding new alternatives can change the rank of the old ones. These rank reversals do not occur often, but the possibility of their occurrencehassubstantial logical implications about the methodology used to make decisions, the underlying assumptions of various decision theories, etc.A simple example will demonstrate the phenomenon of rank reversal: Consider a pretty girl in a small town. She's having a party next week, and she wants to buy a dress that will impress her guests. She visitsthe town's only dress store and goes to the rack of party dresses. There are five such dresses, and after long consideration she ranks them by desirability as follows:Rank Style Color Price1 Style A Blue $1092 Style A Green $1093 Style B Red $1194 Style C Yellow $995 Style D Off-White $149Now imagine that she enters the back room and sees the store'sentire inventory of dresses. The dresses she has looked at in Styles B, C, and D are the only ones of their kind, but there are four more StyleA dresses in green and eight more Style A dresses in blue. In the language of decision science, these dresses are copies of the existing alternatives. In our one-store small town scenario, there's a reasonable chance that one or more party guests would buy and wear one of the copies.When made aware of these new alternatives, our fashion-consciousgirl might rank her choices in a different order. Considering her great embarrassment if a guest were to wear the same dress that she did, she might rank her choices like this:OldRank Style Color PriceRank1 3 Style B Red $1192 4 Style C Yellow $993 5 Style D Off-White $1494 2 Style A Green $1095 1 Style A Blue $109Notice that the rankings of the two Style A dresses have reversed (since there are more copies of the blue dress than of the green one). Not only that, but Style A has gone from the most preferred style to the least preferred. Rank reversal has occurred. Axioms of decision theories have been violated. Scholars and researchers can cry"foul," or impugn the method by which the girl has made her choice, but there is no denying that in the world of our example, ranks havebeen reversed. There is no doubt that the reversal is due to the introduction of additional alternatives that are no different from the existing ones.The above is but one example of rank reversal. Rank reversal canalso occur when additional alternatives are added/removed that are not copies of the original alternatives (e.g., red and yellow dresses in completely different styles). Another example of rank reversal occurred in the 2000 U.S. presidential election. Ralph Nader was an 'irrelevant' alternative, in that he was dominated by both the Democrat and Republican candidates. However, since he attracted more votes from those who would have voted Democrat rather than Republican, his presence caused the ranks to reverse. Put another way, if Nader were not in the race, it is widely accepted that Al Gore would have won.There are two schools of thought about rank reversal. One maintains that new alternatives that introduce no additional attributes should not cause rank reversal under any circumstances. The other maintains that there are both situations in which rank reversal is not reasonable as well as situations where they are to be expected. The current version of the AHP can accommodate both these schools — its Ideal Mode preserves rank, while its Distributive Mode allows the ranks to change. Either mode is selected according to the problem at hand.层次分析法层次分析法(AHP)是一种帮助人们处理复杂决策的结构化技术，比起一种指定的“正确”的方法，层次分析法能帮助人们决定哪一种是更适合他们的需求。

层次分析法的概念

层次分析法的概念层次分析法（Analytic Hierarchy Process，简称AHP）是一种多准则决策分析（Multi-Criteria Decision Analysis，简称MCDA）的方法，由美国运筹学家Thomas L. Saaty于20世纪70年代初提出。

AHP方法通过对多个准则进行层级划分和比较，并运用数学计算方法来确定各准则的重要性和不同方案的优先级，从而帮助决策者做出合理的决策。

AHP的基本思想是将复杂的决策问题分解为多个层次，从上到下逐级进行划分，形成一个层次结构模型。

在层次结构模型中，最顶层为目标层，下面的层次依次为准则层和方案层。

目标层描述了整体决策的目标，准则层描述了实现目标所需要的具体准则，方案层描述了可选方案。

每个层次都有若干个元素，分别构成了一个层次结构的树状图。

AHP方法的核心是构建准则间的判断矩阵，并计算出准则的权重。

判断矩阵用来比较和度量层次结构中的元素之间的重要性和优先级，它的维数等于层次中元素的个数，矩阵元素表示了两个元素之间的相对重要性。

决策者通过对每对元素进行两两比较，根据自己的主观判断，利用语义比例尺（由1到9的9个数值构成）对元素的相对重要性进行评价。

评价结果填入判断矩阵中，形成一个与层次结构对应的判断矩阵。

然后，通过计算判断矩阵的特征向量和最大特征值，可以得到准则的权重。

AHP方法还可以计算各个方案的优先级。

在方案层构建判断矩阵的过程中，同样可以通过两两比较不同方案，评价它们的优先级。

根据方案的判断矩阵，结合准则的权重，运用数学计算方法，可以得到每个方案的优先级权重。

这样，决策者可以根据方案的优先级权重，评估和比较各个方案的可行性和优劣程度，作出决策。

AHP方法的主要优势在于能够将复杂的决策问题进行层次化的细分，从而使决策问题更加清晰和可操作。

它考虑了决策者的主观权重评估和相对重要性比较，充分考虑了不同准则和方案之间的相互关系。

此外，AHP方法还能够处理不确定性和模糊性的问题，对决策者的专业知识和经验有较高的要求，同时也可以用来解决多个决策者之间的决策问题。

层次分析法的原理及应用

层次分析法的原理及应用层次分析法（Analytic Hierarchy Process，简称AHP）是一种定量分析方法，用于解决决策问题，其原理主要基于层次结构和逐级比较的思想。

AHP通过将决策问题分解为多个层次，设立目标层、准则层和方案层，并通过对层次中各元素进行两两比较和权重计算，从而得出最优方案。

AHP的基本原理如下：1.定义层次结构：将复杂的决策问题分解为目标、准则和方案三个层次。

目标是最终要达到的结果，准则是达到目标所需要满足的条件，方案是实现准则的具体行动或选择。

2.建立判断矩阵：通过两两比较的方式，将每个准则和方案与其他准则和方案进行比较，得出相对重要性的判断矩阵。

在比较过程中，根据专家判断，使用1到9的尺度进行评分。

例如，如果A相对于B很重要，则评分为9，如果A和B相等重要，则评分为13.计算权重：根据判断矩阵，通过特征向量法或特征值法计算每个准则和方案的权重。

特征向量法是将判断矩阵的每一列的平均值作为权重，特征值法是通过计算判断矩阵的最大特征值和特征向量得到权重。

4.一致性检验：通过计算判断矩阵的一致性比率和一致性指标，判断专家意见的一致性。

一致性比率越接近0，说明意见越一致，一致性指标小于0.1时才认为专家意见具有可接受的一致性。

5.综合评价：根据权重和准则的得分，计算每个方案的综合得分，从而选择出最优方案。

1.投资决策：在投资决策中，可以将投资目标、收益预期、风险、投资周期等因素作为准则，不同投资方案作为方案，通过层次分析法计算出最优投资方案。

2.供应商选择：在供应链管理中，可以将供货能力、产品质量、价格等因素作为准则，不同供应商作为方案，通过层次分析法评估供应商的综合能力，选择最合适的供应商。

3.项目评估：在项目管理中，可以将项目目标、成本、资源需求等因素作为准则，不同项目方案作为方案，通过层次分析法评估项目的可行性和优劣。

4.策略制定：在战略管理中，可以将市场需求、竞争优势、组织能力等因素作为准则，不同战略方案作为方案，通过层次分析法制定最佳战略。

层次分析法原理

层次分析法原理层次分析法（Analytic Hierarchy Process，AHP）是一种多准则决策方法，由美国学者托马斯·塞蒂（Thomas L. Saaty）于20世纪70年代提出。

它是一种定性和定量相结合的分析方法，适用于处理复杂的决策问题。

层次分析法原理主要基于对不同层次的因素进行比较和权重分配，从而找到最优的决策方案。

首先，层次分析法将决策问题分解为一个层次结构，包括目标层、准则层和方案层。

在这个层次结构中，目标层是最终要达到的目标，准则层是影响目标实现的因素，方案层是可供选择的解决方案。

通过构建这样的层次结构，可以清晰地理解问题的复杂性，有助于分析和决策。

其次，层次分析法通过构建判断矩阵来比较不同层次的因素之间的重要性。

在判断矩阵中，决策者需要对两两因素进行比较，根据其重要性进行打分。

通过对比较结果进行一致性检验，可以确保决策者的判断是合理和一致的。

然后，层次分析法利用特征向量法对判断矩阵进行特征值分解，从而计算出每个因素的权重。

特征向量法是一种数学方法，可以找到最大特征值对应的特征向量，从而得到每个因素的权重。

通过这种方法，可以 quantitatively 来确定不同因素的重要性，为后续的决策提供依据。

最后，层次分析法利用权重分配来进行决策。

在确定了各个因素的权重之后，可以对不同方案进行评价和比较，从而选择出最优的决策方案。

通过层次分析法，可以将主观的定性因素转化为客观的定量分析，有助于决策者做出科学、合理的决策。

总的来说，层次分析法原理是通过将复杂的决策问题分解为层次结构，通过比较和权重分配来找到最优的决策方案。

它结合了定性和定量分析，可以应用于各种复杂的决策问题，如投资决策、项目选择、供应商评价等。

层次分析法在实际应用中已经得到了广泛的应用，成为了一种重要的决策工具。

在决策过程中，层次分析法可以帮助决策者充分考虑各种因素的重要性，避免主观偏见和盲目决策。

它能够将决策问题分解为易于理解和处理的部分，有助于决策者深入分析和思考。

层次分析法

k 1 0.595 0.277 0.129 3.005 0.003 2 0.082 0.236 0.682 3.002 0.001 3 0.429 0.429 0.142 3 0 4 0.633 0.193 0.175 3.009 0.005 5 0.166 0.166 0.668 3 0
ω
( 3) k
( 3)
=ω
( 3) k
ω .
( 2)
0.595 对于P1： ⋅ 0.263 + 0.082 ⋅ 0.475 + 0.429 ⋅ 0.055 +0.633 ⋅ 0.099 + 0.166 ⋅ 0.110 = 0.300 同样，最后得组合权向量 ω
( 3)
= ( 0.300, 0.246, 0.456 )
CI ( p ) p = 3, 4, L , s CR( p ) = CR( p−1) + ( p) RI 其中CR( 2)为第2层对第1层的一致性比率．最后，当最下层对最上层的一致性比率CR( s ) < 0.1时认为整个层次的比较通过一致性检验．
在旅游问题中，可以计算出CI ( 3) = 0.00176, = 0.58，前面已经有了CR = 0.016, 0.00176 ( 3) 于是可得CR = 0.016 + = 0.019 < 0.1 0.58 通过了组合一致性检验，前面得到的组合权向 RI
1 1 / 2 B1 = 1 / 5 1 1 B3 = 1 / 3 1 1 1 1 B5 = 4 4
5 1 1/ 3 B 3 1 1 2 2 = 8 1 / 2 1 3 1 3 3 1 B = 1 / 3 1 1 3 4 1 / 4 1 1 / 3 1 1 / 4 1 / 4 1 2

层次分析法分析短语

层次分析法分析短语引言层次分析法（Analytic Hierarchy Process，AHP）是一种决策分析方法，用于处理复杂的多目标决策问题。

它可以帮助我们在众多因素之间进行权衡和选择，并提供一个合理可行的决策结果。

本文将介绍如何使用层次分析法来分析短语，以解决语义层次关系和权重问题。

什么是层次分析法？层次分析法是一种结构化的决策方法，它将复杂的多目标问题分解为一系列层次结构，从而更容易理解和处理。

在AHP中，问题被划分为三个主要元素：目标、准则和方案，每个元素又可以进一步细分为子准则和子方案。

通过对这些元素之间的比较和权重分配，可以得出一个整体的评估结果。

AHP的基本原理AHP的基本原理是使用专家判断和主观逻辑来确定不同因素之间的相对重要性。

它的核心思想是通过构造一个层次结构，然后使用成对比较的方法来确定每个元素的权重。

具体步骤如下：1.定义问题的层次结构：确定目标、准则和方案，并将它们组织成一个层次结构。

2.成对比较：用判断矩阵对相邻元素进行两两比较，评估它们之间的重要性。

比较的标准可以是数量、质量、重要性等。

3.构造判断矩阵：将成对比较的结果填入判断矩阵中。

4.求解权重：通过计算特征向量和特征值，求解判断矩阵的最大特征值和对应的特征向量。

5.一致性检验：使用一致性指标来检验判断矩阵的一致性，确保判断矩阵的可靠性。

如何使用AHP分析短语在使用AHP分析短语时，我们可以将短语拆解为几个组成要素进行分析。

以下是一种可能的分析框架：1.目标层：确定分析的目标，例如评估短语的效果或选择适合特定场景的短语。

2.准则层：确定评估短语的准则，例如文字表达力、情感激发能力、易理解度等。

3.标准层：将每个准则细分为具体的标准，例如文字表达力可以分为文笔流畅度、形象生动度等。

4.方案层：具体分析每个短语，并与标准进行比较，确定每个短语在每个标准下的相对重要性。

5.权重计算：通过层次比较和判断矩阵的计算，计算出每个短语在每个标准下的权重。

层次分析法模型外文文献翻译2014年译文2000字

文献出处:Ishizaka A, Labib A. THE ANALYSIS OF THE PROCESS IN DERIVING FURTHER BENEFITS OF AN AHP MODEL [J]. The World Insight, 2014, 22(4): 201-220.（声明：本译文归百度文库所有，完整译文请到百度文库。

）原文THE ANALYSIS OF THE PROCESS IN DERIVING FURTHER BENEFITS OF ANAHP MODELIshizaka A, Labib A.ABSTRACTThis paper deals with evaluation of benefits from the AHP methodology that can improve the quality of the decision making process. In this research effort, evaluation (give second opinions) of another’s assessment of goal is carrie d out, wherein, the criteria assessment is different while keeping the alternatives assessment with respect to each criteria constant, to test if the priority vector of the alternatives is same or different.Keywords: AHP process, subjectivity, pair-wise assessments.1. IntroductionMaking decisions involve evaluating the available alternatives and choosing the right one that meets a desired objective. Underlying assumption is our ability to compare, and measure or assess the value of these alternatives with the respect to the goal at hand. It is one of main functions and responsibilities of senior management in organizations. Decision-making is a fundamental process that is integral in everything we do (Saaty, 2004). It is not surprising to know that one of the main goals of education is to help students/participants in the study to make better decisions and increase objectivity in making such decisions. However, subjectivity cannot be completely eliminated because we interpret and make inferences based on objective assessments of the data.Analytical Hierarchy Process, a decision-making methodology developed by Saaty (1987) is an attempt in this direction. AHP can be used in any situation where the presence of multiple influencing factors and decision criteria make it difficult to understand the interactions among them intuitively. In such cases AHP offers a structured approach to reduce the complexity and help us in making a decision objectively.Saaty (2004) argues that subjective judgments using qualitative parameters are not necessarily inferior to physical quantitative measures. He contends that physical scale measurements only help in interpretation and in our understanding and use of the things that we already know how to measure.Although, AHP is practiced in industry and academics, it presents a few concerns and opportunities for further research. One of the concerns is that subjectivity. Although subjectivity cannot be eliminated completely, with better analysis, objectivity can be improved. In this paper, using the AHP methodology, we propose to evaluate or provide second opinion of another person’s assessment of a goal to improve objectivity. With this approach, the second opinion of the criteria assessment is different while keeping the alternatives assessment with respect to each criteria the same and test if the priority vector of the alternatives is same or different.The remainder of the paper presents a brief literature review about the analytical hierarchy process followed by hypothesis of the study and research design. Following these, we present data presentation and analysis. We conclude the paper with limitations and future scope.2. Literature ReviewThe primary objective of AHP is to classify a number of alternatives by considering a given set of qualitative and quantitative criteria and using pair-wise comparisons/judgments. AHP results in a hierarchical leveling of the quality determinants, where the upper hierarchy level is the goal of the decision process, the next level defines the selection criteria which can be further subdivided into sub criteria at lower hierarchy levels and, finally, the bottom level presents the alternative decisions.Analytic Hierarchy Process (AHP) is one of the multi-criteria decision making methods that was originally developed by Saaty (1987). It is a method to derive ratio scales from paired comparisons to determine relative weights and use them for evaluating alternatives. The input can be obtained from actual measurement such as price and weight or from subjective opinion such as satisfaction feelings and preference. AHP has a provision for a small inconsistency (10%) in judgment because it is difficult to be absolutely consistent. The ratio scales are derived from the principal eigenvectors and the consistency index is derived from the principal eigenvector value (Saaty, 2008).It is well known that AHP is associated with large computing and subjectivity (Rang-guo & Yan-ni, 2004). In an effort to improve quality of decisions, Stern, Meherez, and Hadad (2000) suggested a hybrid approach of using data envelopment analysis (DEA) and AHP to take best of both and avoid pitfalls of each method. The Peters-Zelewski (2008) paper looks at a discussion of the pitfalls of AHP from understanding differences between relative versus absolute measurements, clustering of direct measurements, and integrated view of inputs and outputs.Considering the above research findings, our research objective is to understand the inherent subjectivity of pair-wise comparisons via the tool of reciprocal assessments. And to overcome the subjectivity issue, we propose to use research methodology involving evaluation of second opinion of another person’s assessment of a goal to improve objectivity.3. Hypotheses/ObjectivesOur research goal is to improve the quality of decision using AHP by inserting second opinion of a person’s assessment to examine variations in choosing the alternative.4. Research Design/MethodologyIn this research study, we found that without a strong understanding of the AHP technique, the respondents in the pilot survey found it difficult to provide consistent judgment. Hence, we have sought four pair-wise comparisons for the criteria table and two for each of the project judgments (for every criteria) to derive a consistent set ofall pair-wise comparisons.．Using literature review, Rich (2012), Sulemani (2009), Hibner (2011) and interviews with Scrum Masters, we have derived a prioritized list of factors influencing the success for Scrum projects. Five factors were identified, for assessing their influence and impact on success, Scrum process understanding/compliance (Factor 1), Clarity of Scrum Projects i.e. roles and responsibilities(Factor 2), Effectiveness of Scrum Master(Factor 3),Customer–Degree of Product Owner involvement (Factor 4), Team collaborative environment (Factor 5).．The survey questionnaire included two components: general profile (role in project, years of experience, educational qualification, number of scrum projects, number of scrum masters, type of project, size of organization, and part 2 included AHP parameters for gauging the influence of various factors (mentioned above) on success or failure in Scrum project.．For the pair-wise comparisons we used a verbal scale of moderate, strong, very strong and extreme and neutral and converted them into a numerical scale of 2,4,6,8 respectively. The pair-wise comparisons for two respondents are shown in Appendix.对层次分析法AHP模型优势的进一步分析伊扎卡；拉比的摘要本文探讨了层次分析法AHP分析模型的优势，即可以提高企业管理人员决策过程的质量。

层次分析方法范文

层次分析方法范文层次分析方法（Analytic Hierarchy Process，AHP）是一种多属性决策分析方法，它最初由美国运筹学家托马斯·L·赛蒂（Thomas L. Saaty）于1970年提出，并于1980年代得到了广泛应用。

该方法将任务分解为一系列决策层次，在每个层次上比较和权衡不同的因素，并根据这些因素的重要性进行决策。

AHP的基本思想是通过对决策层次结构进行定量化的评估，将主观的判断转化为数值化的数据，从而建立了数学模型，帮助决策者做出理性的决策。

在AHP中，决策层次结构是由目标层、准则层和方案层组成的。

目标层代表决策的最终目标，准则层代表实现目标所需的评价标准，而方案层则代表用来实现目标的各种备选方案。

AHP的核心是建立一个判断矩阵，通过对不同因素的两两比较，得出它们之间的重要程度。

这个比较可以通过两两对比来进行，也可以通过用专家进行问卷调查来获取。

在两两比较的过程中，赛蒂提出了一套尺度，被称为AHP尺度。

这个尺度将因素的重要性评价划分为9个级别，从1（无差别）到9（极其重要），同时还有中间的数值用来描述两个因素之间的相对重要性。

得到判断矩阵后，可以通过特征值法来计算出每个因素的权重。

最终，利用这些权重，可以进行综合评价和决策。

AHP方法适用于多目标、多因素的决策问题，特别是当决策者需要综合考虑不同因素的重要性时，它能够提供一种有效的决策支持方法。

它在工业、经济、管理等领域有广泛的应用，例如项目选择、供应商评估、产品设计等。

AHP方法的优点包括：易于理解和实施、可以处理多个目标和因素、能够反映决策者的主观权重和偏好、可以适应不同的决策层次结构等。

然而，AHP方法也存在一些问题和局限性。

首先，它需要决策者进行大量的两两对比和数值评价，这对于一些复杂的决策问题来说可能是困难的。

其次，AHP方法的结果高度依赖于判断矩阵的构造，如果判断矩阵存在误差或者不一致性，可能会导致不准确的决策结果。

小波分析中英文对照外文翻译文献

小波分析中英文对照外文翻译文献(文档含英文原文和中文翻译)译文：一小波研究的意义与背景在实际应用中，针对不同性质的信号和干扰，寻找最佳的处理方法降低噪声，一直是信号处理领域广泛讨论的重要问题。

目前有很多方法可用于信号降噪，如中值滤波，低通滤波，傅立叶变换等，但它们都滤掉了信号细节中的有用部分。

传统的信号去噪方法以信号的平稳性为前提，仅从时域或频域分别给出统计平均结果。

根据有效信号的时域或频域特性去除噪声，而不能同时兼顾信号在时域和频域的局部和全貌。

更多的实践证明，经典的方法基于傅里叶变换的滤波，并不能对非平稳信号进行有效的分析和处理，去噪效果已不能很好地满足工程应用发展的要求。

常用的硬阈值法则和软阈值法则采用设置高频小波系数为零的方法从信号中滤除噪声。

实践证明，这些小波阈值去噪方法具有近似优化特性，在非平稳信号领域中具有良好表现。

小波理论是在傅立叶变换和短时傅立叶变换的基础上发展起来的，它具有多分辨分析的特点，在时域和频域上都具有表征信号局部特征的能力，是信号时频分析的优良工具。

小波变换具有多分辨性、时频局部化特性及计算的快速性等属性，这使得小波变换在地球物理领域有着广泛的应用。

随着技术的发展，小波包分析(Wavelet Packet Analysis)方法产生并发展起来，小波包分析是小波分析的拓展，具有十分广泛的应用价值。

它能够为信号提供一种更加精细的分析方法，它将频带进行多层次划分，对离散小波变换没有细分的高频部分进一步分析，并能够根据被分析信号的特征，自适应选择相应的频带，使之与信号匹配，从而提高了时频分辨率。

小波包分析(wavelet packet analysis)能够为信号提供一种更加精细的分析方法，它将频带进行多层次划分，对小波分析没有细分的高频部分进一步分解，并能够根据被分析信号的特征，自适应地选择相应频带,使之与信号频谱相匹配，因而小波包具有更广泛的应用价值。

利用小波包分析进行信号降噪，一种直观而有效的小波包去噪方法就是直接对小波包分解系数取阈值，选择相关的滤波因子，利用保留下来的系数进行信号的重构，最终达到降噪的目的。

医药物流供应链中英文对照外文翻译文献

医药物流供应链中英⽂对照外⽂翻译⽂献中英⽂对照外⽂翻译⽂献(⽂档含英⽂原⽂和中⽂翻译)译⽂：标题：伊朗市药品供应链风险评估(层次分析法和简易加权法)摘要⽬标：在供应药品过程中，药品供应链是卫⽣系统的重要组成部分，在⼤多数国家，主要药物由当地制药公司提供。

在评估药品供应链过程中，虽然不存在以往的评估风险研究对制药企业风险和评估的⼲扰，但任何影响医药企业的风险都可能会破坏供应药品和医疗系统的效率。

这项研究的⽬标是评估伊朗医药⾏业的风险，考虑进程的优先级，风险和风险的概率。

⽅法：对4个阶段进⾏研究，通过⽂献回顾、专家访谈、风险分析等⽅法，通过问卷调查、专家咨询、专家分析、专家访谈、风险分析等⽅法，采⽤层次分析法、评定量表法和简易加权重法进⾏风险评价。

结果：总的来说，从药品供应链的⾓度来看，86个主要风险被制药公司分为11类。

在这项研究中，⼤量风险描述与⾦融和经济范畴相关。

同时财务管理被认为是最重要的因素考虑。

结论：在研究期间，虽然医药⾏业和供应链的受到伊朗当前政治因素的影响，但医药供应链中的总风险的⼀半，仍被认为是内部风险，可以定位到公司的内部。

我们可以看出，政治因素和相关的风险迫使企业更加注重财务和供应管理，导致质量管理⽅⾯的疏忽。

关键词：医药供应链，风险评估，层次分析法，简单相加加权法，伊朗医药产业简介药品供应是发展中国家的主要优先事项之⼀。

因此，有效的药品供应链管理是⾮常重要。

⼀个⾼效的药品供应链，是在适当的时间，以最佳的价格为客户提供满意质量，正确数量的药品物资⽽产⽣的所有利益相关者的利益药品供应链是健全⽅案的重要组成部分，其中包括所有的程序，信息，资源和参与者如供应商，制造商，中间商，第三⽅服务提供商，物流活动，营销和销售活动，财务和信息技术的医疗卫⽣规划。

制药公司在供应药品⽅⾯发挥重要的作⽤，特别是供应量由本地公司提供的。

制药公司在伊朗有重要的作⽤，在供应链中，95％以上的药品市场（以体积计算），是由本⼟⼚商提供的。

外文翻译---利用层次分析法选择各类发电厂

英文原文Multi-criteria selection of electric power plants using analytical hierarchy processAbstractThis paper uses analytical hierarchy process (AHP) methodology to perform a comparison between the different electricity power production options in Jordan. The systems which were considered, in addition to fossil fuel power plants, are nuclear, solar,wind, and hydro-power. Results on cost to benefit ratios show that solar, wind, end hydro-power may be the best alternatives for electric power production. Nuclear electricity turns out to be the worst choice, followed by fossil fuel electric power.1. IntroductionJordan is a non-oil producing Middle-Eastern country. It relies heavily on importing oil from neighboring countries. Most of the electric power that is generated to serve different sectors of the country is produced from power plants that use fossil fuel. This fuel is either totally imported such as petroleum hydrocarbon fuel, or partially local (only with small percentage) such as natural gas. The 1996 electrical energy consumption in Jordan reached a value of 6000 GWh. About 93% of his amount was produced by the National Electric Power Company (NEPCO) which is the main electricity supplier in the country [1]. Other options or alternatives of energy sources for electric power generation must tee considered. These options may include nuclear, solar, wind, or hydro-electric energies. The Jordanian experience with electricity generation using solar and windenergy technology has been on the small and experimental scale. These renewable energy systems were utilized in mostly remote areas of Jordan. They are used to generate electric power for individual application such as clinics, lighting, and educational television sets. The remote village of Jurf Eldaraweesh located in the Jordan desert of a population of 600, is the best example [2]. The necessary electrical energy is totally supplied by solar and wind energy conversion systems.In this paper, oil-fired power plants in addition to other alternatives are being evaluated. The other alternatives include nuclear, solar, wind and hydro-power. A brief description of various power plant technologies will be presented. Using a decision-support system through a multiple criteria analysis, such as AHP, an attempt will be made to assist decision makers to evaluate the use of the above technologies which can be most suitable for electrical power production in Jordan.2. Fossil-fuel electrical power plantsIn general, fossil fuels are non-renewable. They originate from the earth as a result of decomposition and chemical conversion of organic materials. They come in three organic forms: (1) solid, e.g. coal and oil shale; (2) liquid, e.g. most petroleum products, and (3) gas, e.g. natural gas. Coal represents the largest fossil-fuel energy resource in electric power generation [3,4]. Oil shale is a fossil fuel that exists in Jordan in abundance, but with unattractive physical properties. First, like all oil shales, it has a low heating value due to the high ash content [5]. Secondly, the Jordanian oil shale has sulfur contents, ranging 4–6% [6]. Because of low prices of petroleum world wide the utilization of solid fossil fuels, such as oil shale, cannot be feasible at the time being.Therefore, oil shale power plants can not be considered to be competitive [3]. Petroleum and natural gas are the main fuels used for the electric power generation in Jordan in addition to small hydro-powered electricity generation plants. Table 1 represents the existing electrical power plants in Jordan [1].3. Electricity power production using solar energySince the 1970s solar energy has received the greatest attention of all renewable energy sources all over the world. Many regard it as the solution for cleaner environment and may be the alternative to fossil and nuclear fuels. Thus, solar energy has been the object for production of electrical power. Many studies and experiences have shown that solar thermal power plants are one of the most economic forms of solar electricity generation. Solar energy can be converted into electricity by photovoltaic cells, but this process is mostly convenient and suitable for small applications only. Stand alone photovoltaic power systems were proposed for electrification of remote areas of which they are located outside the electricity grid-connection supply system [7]. On the other hand, solar energy can be converted into thermal energy by means of solar collectors or concentrators. A working fluid is used to convert the thermal energy into mechanical energy which is then converted into electricity. Unlike photovoltaics, large amounts of electrical power can be generated from such plants. The types of receivers that can be seriously considered are: (1) central receivers, (2) dispersed or distributed receivers and (3) solar ponds. Like most countries of the Middle East, Jordan enjoys long periods of sunshine. The local weather has over 300 cloudless days per year. Future technology suggests that the Dead Sea itself can be used as 450 km2 solar lake, operating a 2500 MWpower plant [8]. In a recent study, the potential of using the Dead Sea as a large natural solar pond for generation of electricity in Jordan was explored [9]. Kribus et al. [10] have shown new solar power plant concept by incorporating new developments of solar power optics, high performance air receivers, and solar-to-gas turbine interface. In terms of economical point of view, Kolb [11] found hybrid power towers to be superior to solar-only plants with the same field size. There is a number of solar thermal power plants in operation around the world. They are found to be one of the most economical systems for generating electricity [12,13]. Recently, the co-generation of electricity and potable water by utilization of solar energy was carried out [14,15]. This kind of system looks attractive in remote areas where both water is scares and electricity grid is not available. The system is capable of producing 30 MWe or more.4. Electrical power production using wind energyIt is very well established that wind energy resource is large and globally widespread. For different applications, it is clear that wind energy can be competitive in many locations [16–18]. Wind energy can be used in many applications such as water pumping [19], and water desalination [20]. It can also be used for the electrical power generation using wind energy conversion system [21]. Wind power is expected to be one of the least expensive forms of new electrical generation in the twenty-first century [22].With global efforts to become tough on fossil fuel related energy systems and to reduce the emissions of CO2 significantly, this will most likely introduce lower cost wind systems. For example, large wind power plants at good wind sites using emerging technologies can deliver electricity into utility grid at low prices that are becomingcompetitive with those of conventional power generation. Wind power plants can use hundreds of wind turbines that range in size from 50 to 500 kW each located in some remote areas. The plant’s computerized and control center operates similar to fossil fuel plants, except it does not have to be in sight of turbines. In a recent study a model of wind power plant for isolated location was presented [23]. Increases in the prices of fuel and cost of fossil fuel plants and in relying less on non-renewable energy resources, decrease the value and cost of wind power generation systems significantly [24,25].There are number of sites in Jordan with potentially high wind speeds, that can be utilized for this purpose [26,27]. Habali et al. [27] have presented an evaluation of wind energy in Jordan and its application for electrical power generation. A total of 11 wind sites were considered covering the entire country. The three most potential sites in Jordan are found to be Ras Muneef, Mafraq, and Aqaba. They have wind speeds that range from 4 to 23 ms throughout 80% of the whole year.5. Hydro-electric power plantsHydro-electric power plants can provide a basis for evaluating the potential of renewable sources of energy. When compared to other thermal power plants, they are found to be conventional and reliable. Some countries utilize this form of free natural energy into useful type of electrical power. For example, 11% of the electric power produced in the USA was provided by hydro-electric power [4]. Egypt and Turkey, countries of this region, also utilize this type of power for generating electricity at low costs.A number of studies were involved in utilizing hydro-power in Jordan for thepurpose of electricity production [28], water desalination [29,30], and both electricity production and water desalination [8,31]. These studies, mainly, considered the linkage of Red and Dead Seas with a canal to generate hydro-power. The Dead Sea is about 400 m below sea level (BSL), it is roughly 200 km to the north of the Gulf of Aqaba. It is an extension of the Red Sea. The Dead Sea has no outlet; its water level is a function of inflow and evaporation of water. For thousands of years the Dead Sea maintained an equilibrium with the annual inflow and evaporation of water. This resulted in a constant sea level. For example, in 1930 the surface of the Dead Sea was measured at its historical elevation of about 390 m BSL. The Jordan River is considered to be the main tributary of the Dead Sea. Over the years due to increase in population and agricultural development, water was diverted for irrigation in the Jordan Valley and neighboring countries. Therefore, its elevation was forced to drop, drastically; in 1993 it was 408 m BSL. To halt this trend, it will be necessary to introduce a substantial amount of new water to the sea. Sea water from the Red Sea can be used as a source of wafer needed for diversion into the Dead Sea. This diversion can be used to either maintain the sea at its current level and thus stop its dropping, or even to bring it back to its historical level. The power obtained from such process can be used to generate electricity and allow even more fresh water to be diverted from the Jordan River.6. Nuclear power plantsIt is very well known fact that for those countries that rely on but do not have oil, nuclear power becomes a strategic as well as economic necessity [3]. Nuclear power plants can pay for their capital cost in a few short years. Thus, a less expensive electricpower can be produced without relying on importing foreign oil, or at least the reduction in oil import. Some believe that one day oil will be depleted, and nuclear power becomes a must. Therefore, it is important to start this technology now in order to assure the country would not be left behind when the time comes to have to use nuclear technology.Nuclear electricity offers an advantage from an environmental point of view and air pollution. It has less environmental problems that are associated with oil-fired power plants. Thus, nuclear power is bound to become the choice of power for the future. There are some difficulties that are associated with nuclear power, namely, waste disposal and safety. If this kind of energy becomes popular in most countries around the world, solutions to these problem become a must and thus be found.7. The analytic hierarchy processThe analytic hierarchy process (AHP), which was developed by Saaty [32], has been an effective tool in structuring and modeling multi-objective problems. For example, it has been applied to business decisions [33], selection of areas of research and development programs [34], real estate investments [32], water policies [35], and water desalination technologies [29]. AHP can assist decision makers to evaluate a problem in the form of a hierarchy of references through a series of pairwise comparisons of relative criteria. Briefly, relative weights are determined through pairwise comparison. The method can be applied by breaking down the unstructured complex scorecard problems into component parts. Hierarchical orders are then arranged by forming value tree structures. Subjective judgments on the relative importance of each part are representedby assigning numerical values; the numerical values are selected in accordance to Fig. 1. These judgments are then synthesized in the use of eigenvectors to determine which variables have the highest priority.The decision regarding the selection of an optimum system for electricity power generation in Jordan was evaluated according to benefits and costs. Cost-tobenefit analysis is obtained by separating costs from benefits and structuring separate hierarchies for benefits and costs. They were constructed as shown in Figs. 2 and 3. The overall objective (goal) for both hierarchies was to select an optimum system (i.e. level1). Fig. 2 shows the cost hierarchy. The cost criteria at level 2 are cost of fuel, hardware cost, maintenance and service, auxiliary system, and environmental constraints.Fig. 3 presents the benefit hierarchy, it includes all possible benefits that may be derived from the various electrical power generation power plants, as applied to Jordan. Level 1 of Fig. 3 is the selection of the optimum system in terms of benefits. The benefit criteria at level 2 are the efficiency of the system, its reliability, its safety, availability of the fuel used in the system, its effect on national economy, and social benefits.The third level of the cost and benefit hierarchies represents the various technologies or alternatives which are going to be considered for electrical power production in Jordan. In addition to fossil fuel fired power plants these systems include nuclear, solar, wind, and hydro-power.8. Results and discussionFig. 2 shows that nuclear and fossil fuel power plants have the highest cost, with relative weights of 0.429 and 0.337, respectively. On the other hand solar, wind, andhydro have much lower values of relative weights in the range of 0.077–0.079. It is based on the cost hierarchy which indicates that cost of fuel has the highest relative weight of 0.375 among all other costs considered. It is followed by hardware and maintenance costs; their relative weight is 0.215 each. Environmental constraints and the need of auxiliary system have the lowest relative weights with values of 0.122 and 0.074, respectively.Benefits hierarchy (Fig. 3) shows that fossil fuel power plant has the most benefits having a relative weight of 0.255. It is followed by solar and wind power plants; their corresponding relative weights are 0.162 and 0.130, respectively. System’s reliability has the highest relative weight of 0.365. It is followed by availability of fuel, system’s efficiency, its effect on national economy, safety and then social benefits.In order to give the complete picture the overall cost priorities (relative weights) were divided by the benefit priorities. An overall normalized cost-tobenefit ratio was obtained for each system. They are presented in Fig. 4. It is shown that nuclear electrical power plants have the highest overall cost-to-benefit ratio, with a relative weighs value of 0.57. Fossil fuel power plants have the second relative weight of about 0.23. The best systems with lowest cost-to-benefit ratios are solar, followed by wind and then hydro having relative weights of 0.058, 0.061, and 0.083, respectively.9. ConclusionsBased on AHP, solar electrical power plants have the potential to be the best type of system for electricity production in Jordan. They are followed by wind and then hydro-power plants. One can argue that all three technologies or any of the twocombined can be used since they have close relative weights. On the other hand nuclear power plants have the worst rating and fossil fuel power plants are some what little better than nuclear.中文译文利用层次分析法选择各类发电厂摘要本文运用层次分析法(AHP)详细地介绍了利用不同能源进行发电。

翻译项目流程

翻译项目流程翻译项目流程是指在进行翻译工作时所需遵循的一系列步骤和流程，以确保翻译成果的质量和准确性。

下面将详细介绍一个标准的翻译项目流程。

1. 项目准备阶段：在项目准备阶段，需要明确项目的背景、目标和要求。

首先，与客户进行沟通，了解项目的背景信息，包括翻译的语言对、主题领域、文本类型、数量和交付时间等。

然后，与客户商讨项目的目标和要求，明确翻译成果的质量标准、格式要求以及其他特殊要求。

2. 项目分析阶段：在项目分析阶段，需要对待翻译的文本进行分析和评估。

首先，对文本进行初步了解，包括内容、结构和风格等。

然后，进行术语和专业词汇的收集和整理，以便在翻译过程中使用。

此外，还需评估翻译难度和风险，确定是否需要其他专业人员的支持。

3. 翻译阶段：在翻译阶段，根据项目要求进行翻译工作。

首先，进行术语和词汇的研究和理解，确保准确使用。

然后，按照文本的语言风格和表达习惯进行翻译，注意语法、语义和语用等方面的准确性。

同时，还需保持翻译的一致性和连贯性，确保整个文本的流畅性和可读性。

4. 校对阶段：在校对阶段，对已翻译的文本进行校对和修订。

首先，进行语法、拼写和标点等方面的校对，确保文本的语言规范和准确性。

然后，进行内容和结构的校对，确保翻译的一致性和完整性。

此外，还需进行格式和排版的校对，确保文本的整体美观和规范。

5. 审核阶段：在审核阶段，由专业人士对翻译成果进行审核和评估。

首先，进行术语和专业词汇的审核，确保使用准确和一致。

然后，进行语言和风格的审核，确保翻译的质量和准确性。

此外，还需进行内容和逻辑的审核，确保翻译的准确表达和完整传达。

6. 交付阶段：在交付阶段，将翻译成果交付给客户。

首先，进行最终的整理和校对，确保翻译的完整性和准确性。

然后，按照客户要求的格式和方式进行交付，包括电子文档、打印文件或在线发布等。

此外，还需提供相关的附加信息和说明，以便客户更好地使用和理解翻译成果。

7. 反馈和改进阶段：在交付后，与客户进行反馈和沟通，了解客户对翻译成果的满意度和意见建议。

层次分析法的实施步骤

层次分析法的实施步骤引言层次分析法（Analytic Hierarchy Process，AHP）是一种多标准决策方法，由美国学者托马斯·萨帕索（Thomas Saaty）于20世纪70年代提出。

它通过将问题分解为多个层次，建立层次结构模型，进行准则间的两两比较，最终得出权重的相对优先级，从而辅助决策者做出决策。

本文将介绍层次分析法的实施步骤，以帮助读者了解如何在实际应用中使用这一方法。

步骤1. 确定目标和准则在使用层次分析法之前，首先需要明确决策的目标和准则。

目标是希望实现的成果，而准则是评估和判断目标实现程度的标准。

例如，如果我们要选择一个新的供应商，我们的目标可以是寻找质量最好、价格最合理、交货速度最快的供应商。

准则可以是质量、价格和交货速度。

2. 建立层次结构模型在确定目标和准则后，下一步是建立层次结构模型。

层次结构模型是一个图形表示，将目标和准则按照层次关系进行组织。

层次结构模型由三个层次组成：目标层、准则层和方案层。

目标层是最高层，表示决策的最终目标；准则层是中间层，包含评估和判断目标实现程度的准则；方案层是最低层，包含备选方案或决策选项。

3. 两两比较准则在建立层次结构模型后，决策者需要对准则进行两两比较，以确定它们之间的相对重要性。

比较的方法通常采用1到9的标度，其中1表示两个准则之间的重要性相等，9表示一个准则相对于另一个准则非常重要。

其他数字表示中间的权重关系。

决策者可以使用判断矩阵记录这些比较结果。

判断矩阵是一个n×n的矩阵，n是准则的数量。

矩阵的每个元素代表两个准则之间的比较结果。

4. 计算权重向量通过两两比较准则后，接下来需要计算权重向量，以确定每个准则对于目标的相对重要性。

计算权重向量的方法是通过对判断矩阵进行数学处理，得出每个准则的权重。

5. 一致性检验在计算权重向量后，需要进行一致性检验，以判断判断矩阵中的比较结果是否合理和一致。

一致性指标是一个反映判断矩阵一致性的数值，通常表示为CI。

SOWStatementofWork项目管理名词解释（SOW）

SOWStatementofWork项⽬管理名词解释（SOW）SOW:英⽂全称statement of work（⼯作说明）。

是合同的附件之⼀，具有与合同正⽂同等的法律效⼒。

⼯作说明详细规定了合同双⽅在合同期内应完成的⼯作，如⽅案论证、设计、分析、试验、质量控制，可靠性、维修性、保障性、标准化、计量保证等；应向对⽅提供的项⽬，如接⼝控制⽂件、硬件、计算机软件、技术报告、图纸、资料，以及何时进⾏何种评审等下⾯是SOW有下⾯四种常见形式：功能：客户通常知道他们想要什么，但不知道怎么达到他们想要的⽬标。

功能SOW确定客户在最后交付产品时想要什么。

性能：这是SOW最常见的形式。

它详细说明协约的所有交付的产品，确定流程、范围和可接受的努⼒等级。

这集中在整个协约。

设计：在设计SOW中，客户已经很详细地描述服务或交付产品怎样获得、建⽴、实现等等，主要集中在流程和设计上。

增加：⼀个企业组织⼀般需要资源⽀持开发。

这样就需要完成⼀个⼈员增加SOW，⽤以详细说明由承包⼈完成的⼯作范围、客户对承包⼈技能、资格认证和⼯作质量的期望。

典型的SOW包含以下的内容：封⾯：包含项⽬标题、合同信息、修订号和作者⽬录：在⼤型SOW中证明⾮常有⽤简介：包含项⽬的总览和背景定义或者术语表：定义关键词或者不明确的术语项⽬范围：确定项⽬范围以及与其它项⽬的关系⽬标和⽬的：说明根据SOW你想得到什么参考⽂献：包含⼀个附属的或者所参考的⽂档的⼀个概要⼯作描述：详细说明⼯作范围，要完成的⼯作等等。

细分来看通常包括：需求、技术规范说明、质量标准、⽅法、开发标准、交付产品、性能测量、报告需求、安全性、例⼦、插图、数据处理约束等等⼯作地点：描述在什么地⽅完成⼯作，还有怎么到达⼯作地点、讨论室、开会地点、电话、桌⼦、PC、软件等等安全：列出对要⼯作的资源的安全限制出差或者住房：详细说明出差和⾷宿预算限制交付产品：列出期望的产品或者切实的结果计划或者产品进度表：有关项⽬计划更加详细的特性，包括WBS、资源、时限、交付进度和⾥程碑。

翻译项目流程

翻译项目流程引言概述：翻译项目流程是指在进行翻译工作时，按照一定的步骤和流程进行的管理和执行过程。

合理的翻译项目流程可以提高翻译质量、保证项目进度和控制成本。

本文将详细介绍翻译项目流程的五个部分。

一、项目准备阶段：1.1 确定项目需求：与客户沟通，了解项目背景、目的、要求和交付时间等，确保明确项目需求。

1.2 确定翻译资源：根据项目需求，确定所需的翻译资源，包括翻译人员、术语库、翻译工具等。

1.3 制定项目计划：根据项目需求和资源情况，制定详细的项目计划，包括项目时间表、人员分工和任务分配等。

二、翻译执行阶段：2.1 文档分析：对待翻译文件进行仔细分析，了解文档内容、格式和特点，为后续翻译工作做好准备。

2.2 术语管理：建立术语库，统一术语翻译，确保翻译的一致性和准确性。

2.3 翻译和校对：根据项目计划，翻译人员进行翻译工作，并由校对人员对翻译结果进行审核和修改，确保翻译质量。

三、质量控制阶段：3.1 内部审校：由内部审校人员对翻译结果进行审查，检查翻译的准确性、一致性和流畅性等。

3.2 客户反馈：将翻译结果交付给客户，征求客户的反馈意见，及时进行修改和调整。

3.3 最终审校：在客户反馈的基础上，进行最终的审校工作，确保翻译结果符合客户要求和标准。

四、交付阶段：4.1 格式整理：对翻译结果进行格式整理，保证文档的可读性和美观性。

4.2 文件交付：将最终的翻译结果按照客户要求进行打包和交付，确保项目按时完成。

4.3 项目总结：对整个翻译项目进行总结和评估，总结经验教训，为后续项目提供参考。

五、售后服务阶段：5.1 客户满意度调查：对客户进行满意度调查，了解客户对翻译项目的评价和意见，为提供更好的服务做准备。

5.2 建立长期合作关系：通过及时回访和沟通，建立长期稳定的合作关系，为客户提供持续的翻译服务。

5.3 不断改进：根据客户反馈和项目总结，不断改进翻译项目流程，提高翻译质量和效率。

结论：翻译项目流程是保证翻译质量和项目进度的重要管理工具。

翻译项目流程

翻译项目流程标题：翻译项目流程引言概述：翻译项目流程是指在进行翻译工作时所需要遵循的一系列步骤和流程。

一个完整的翻译项目流程能够确保翻译质量和效率，提高工作效果。

在翻译项目中，翻译人员需要按照一定的流程进行工作，从而保证翻译结果的准确性和一致性。

一、项目准备阶段1.1 确定项目需求：在项目准备阶段，首先需要明确项目的翻译需求，包括翻译内容、语种、交付时间等。

1.2 确定团队成员：确定项目团队成员，包括翻译人员、校对人员、项目经理等，确保团队的合作和协调。

1.3 制定项目计划：制定详细的项目计划，包括翻译进度、质量控制、沟通方式等，确保项目按时高质量完成。

二、翻译执行阶段2.1 翻译文本分析：对待翻译文本进行仔细分析，了解文本内容、语境和特点，为后续翻译工作做好准备。

2.2 术语管理：建立术语库，统一术语翻译，确保翻译结果的一致性和准确性。

2.3 翻译质量控制：在翻译过程中进行质量控制，包括自我校对、同行校对等，确保翻译质量符合要求。

三、校对审校阶段3.1 校对工作：由专业校对人员对翻译文本进行校对，发现并纠正翻译错误和不准确之处。

3.2 语言审校：进行语言审校，确保翻译结果符合语言习惯和表达规范。

3.3 格式审校：进行格式审校，确保翻译文本的格式和排版符合要求。

四、交付阶段4.1 交付前检查：在交付之前对翻译文本进行最后检查，确保没有遗漏和错误。

4.2 交付方式：根据项目要求选择合适的交付方式，包括电子邮件、云盘等。

4.3 交付后反馈：接收客户反馈，及时处理客户提出的问题和建议，确保客户满意。

五、项目总结阶段5.1 项目总结：对整个项目进行总结和评估，总结经验教训，为以后的项目提供参考。

5.2 团队反馈：收集团队成员的反馈意见，改进工作流程和提高工作效率。

5.3 客户满意度调查：进行客户满意度调查，了解客户对翻译质量和服务的评价，为提升服务质量提供参考。

结语：翻译项目流程是一个复杂而又重要的过程，需要团队成员之间的密切合作和高效沟通。

翻译项目流程

翻译项目流程翻译项目是一项复杂的任务，需要经过一系列的流程来确保翻译的准确性和质量。

以下是一个标准的翻译项目流程，以确保项目的顺利进行和高质量的交付。

1. 项目准备阶段：在这个阶段，项目经理将与客户进行初步沟通，了解项目的需求和要求。

这包括源语言和目标语言，翻译的领域和专业性要求，交付时间等。

项目经理还将与客户商讨项目的预算和支付方式。

2. 项目分析阶段：在这个阶段，项目经理将对项目进行详细分析和评估。

这包括文本的长度和复杂性，是否需要专业领域的译员，是否需要使用翻译记忆工具等。

根据分析结果，项目经理将制定详细的项目计划和时间表。

3. 译前准备阶段：在这个阶段，项目经理将与译员进行沟通，并提供项目的详细说明和要求。

译员将对源语言文本进行研究和理解，以确保准确理解文本的内容和背景知识。

译员还可能进行术语和词汇的研究，以确保翻译的准确性和一致性。

4. 翻译阶段：在这个阶段，译员将根据项目要求进行翻译工作。

译员将使用专业的翻译技巧和工具，如翻译记忆工具和术语库，以确保翻译的准确性和一致性。

译员还可能与项目经理进行沟通，以解决翻译过程中的问题和疑问。

5. 校对和编辑阶段：在这个阶段，经验丰富的校对人员将对翻译的文本进行校对和编辑。

校对人员将检查翻译的准确性、语法和拼写错误，并进行必要的修正和修改。

校对人员还将确保翻译的一致性和风格的统一。

6. 格式排版和质量控制阶段：在这个阶段，专业的排版人员将对翻译的文本进行格式排版和设计。

他们将确保文本的格式和布局与原始文档一致，并进行必要的调整和修改。

质量控制人员将对最终的翻译文本进行全面的质量检查，以确保翻译的准确性和一致性。

7. 最终交付阶段：在这个阶段，项目经理将向客户交付最终的翻译文本。

交付的形式可以是电子文档或打印版，具体根据客户的要求而定。

项目经理还将与客户进行最终的沟通和确认，以确保项目的成功交付。

总结：以上是一个标准的翻译项目流程，其中涵盖了项目准备、分析、译前准备、翻译、校对和编辑、格式排版和质量控制以及最终交付等多个阶段。