基于小波与灰色模型的滑坡时间预测预报

摘要

我国是世界上滑坡灾难最为严峻的国家之一。滑坡灾难往往会造成严峻的经济损失，威胁人民生命安全。据统计，我国有70多个都市，460多个县收到滑坡灾难的威胁及危害，每年平均至少造成15亿—23亿元的经济损失，由于近年来自然灾难增多，滑坡也相应增加。假如我们能够明白滑坡发生的时刻，积极采取应对措施，就能够将滑坡危害降到最低，减少不必要的人员伤亡和经济损失。因此对滑坡时刻进行预测预报研究具有十分重要的意义。本文基于以上目的，针对滑坡预测预报中存在的问题进行时刻预测预报研究。本文要紧通过对小波理论和灰色模型的介绍和研究，将小波降噪和灰色模型应用于滑坡时刻预测预报。要紧研究内容如下：

（1）对滑坡时刻预测预报及其进展趋势做了简单的介绍。介绍了滑坡监测技术和滑坡预测模型。

（2）时刻预测预报之前需要对观测的位移时刻数据进行处理，去除噪声，以提高预测精度。本文选用小波的方法对滑坡观测的位移数据进行去噪处理。在此之前介绍了小波理论，小波函数和小波阈值的选取规则。后面通过选用不同的阈值来对滑坡数

据进行降噪处理，并利用信噪比来比较降噪效果。

（3）简单介绍灰色系统模型，利用matlab编写相应的程序。并利用灰色模型对差不多降噪处理的数据进行时刻预测，并分析结果。

（4）把小波阈值降噪方法和灰色模型应用到新滩滑坡，对观测数据进行降噪处理并预测时刻，并将结果与真实值进行对比分析。

关键词：滑坡小波分析小波阈值灰色模型降噪时刻预测

Abstract

China is one of the countries which have the most serious landslide calamity in the world。Landslide calamity can always cause serious economic losses, which threatens the safety of people's life.According to the statistics, about 70 cities and 460 counties in our country have been threatened and damaged by the landslide hazard. As a result, the economic usually suffers from a loss between at least 1.5 billion and 2.3 billion every year. As the natural disasters increase recently, the landslides also increase accordingly.If we know that the landslide occurred at certain time and take actions, then the landslide hazard can be reduced at most, besides we can reduce unnecessary casualties and economic losses.Consequently, research of forecasting Landslide-time is significant.Based on the purpose above, in this paper, for the problems in the prediction of landslide, we will make a detailed research. According to the introduction and study of wavelet theory

and Grey model, wavelet noise reduction and Grey model can be applied to landslide prediction.The main research contents are as follows:

（1）A succinct introduction of the landslide-time prediction and development tendency, including the landslide monitoring technology and landslide prediction model.

（2）Before theTime prediction, In order to improve prediction accuracy, it is necessary to process observed displacement time data and remove noise. In this paper, the technique of wavelet is applied to remove the noise in the observed landslide displacement data.Wavelet theory, wavelet function and the selection rules of wavelet threshold are proposed before, Then conduct noise reduction for landslide data by different threshold values, besides, through the signal to noise ratio to compare the result of noise reduction.

（3）Proposing Grey model succinctly, programming by MATLAB and using Grey model to estimate the time of the