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区域泥石流危险度评价的影响因子识别
引用本文:苏鹏程,倪长健,孔纪名,汪阳春.区域泥石流危险度评价的影响因子识别[J].水土保持通报,2009,29(1):128-132.
作者姓名:苏鹏程  倪长健  孔纪名  汪阳春
作者单位:苏鹏程,孔纪名,汪阳春,SU Peng-cheng,KONG Ji-ming,WANG Yan-chun(中国科学院,山地灾害与地表过程重点实验室,四川,成都,610041;中国科学院,水利部,成都山地灾害与环境研究所,四川成都610041);倪长健,NI Chang-jian(成都信息工程学院,四川成都,610225)  
基金项目:国家自然科学基金重点项目,水利部公益性行业专项基金,中国科学院成都山地所青年种子基金 
摘    要:区域泥石流危险度评价是环境保护和减灾的重要内容.针对泥石流危险度评价的多因素影响问题,通过全面收集有代表性的泥石流样本资料,应用免疫进化算法,建立了区域泥石流危险度评价的投影寻踪聚类模型.研究结果表明,该模型依据样本自身的数据特性寻求最优的投影方向,并通过投影方向计算反映评价样本综合特征信息的投影特征指标.该模型不但可以确定各评价指标的权重,避免权重人为的任意性,还能在区域泥石流不同危险度级别划分的基础上,以平均贡献率的大小揭示不同影响因子对评价结果的影响,从而可清楚地筛选出其中的关键影响因子.此研究从定量的角度进一步深化了对泥石流危险度评价影响因子的认识.

关 键 词:泥石流  投影寻踪聚类  危险度  贡献率  关键因子
收稿时间:2008/8/12 0:00:00
修稿时间:2008/9/24 0:00:00

Factor Identification for Regional Danger Degree of Debris Flow
SU Peng-cheng,NI Chang-jian,KONG Ji-ming and WANG Yan-chun.Factor Identification for Regional Danger Degree of Debris Flow[J].Bulletin of Soil and Water Conservation,2009,29(1):128-132.
Authors:SU Peng-cheng  NI Chang-jian  KONG Ji-ming and WANG Yan-chun
Institution:Key Laboratory of Mountain Hazards and Surface Processes, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China;Institute of Mountain Hazards and Environment, Chinese Academy of Sciences and Ministry of Water Conservancy, Chengdu, Sichuan 610041, China;Chengdu University of Information and Technology, Chengdu, Sichuan 610225, China;Key Laboratory of Mountain Hazards and Surface Processes, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China;Institute of Mountain Hazards and Environment, Chinese Academy of Sciences and Ministry of Water Conservancy, Chengdu, Sichuan 610041, China;Key Laboratory of Mountain Hazards and Surface Processes, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China;Institute of Mountain Hazards and Environment, Chinese Academy of Sciences and Ministry of Water Conservancy, Chengdu, Sichuan 610041, China
Abstract:Regional evaluation of debris-flow danger degree is an important part of environment protection and disaster reduction.Based on immune evolutionary algorithm and by collecting typical and complete samples,the projection pursuit cluster model(PPC) is established and applied to treat the multi-factor evaluation of danger degree of debris flow.Projection pursuit can project high dimensional data to low dimensional space.Through studying the main characteristics in the 1-D space,the key information in original data can be obtained,which can not only eliminate the subjectivity of the weight of each factor,but also reveal its impacts on the evaluation according to its actual mean contribution rate,based on the classification of different regional danger degrees of debris flow.In this way,the key factors can be clearly selected.The study further deepens the quantitative understanding of the evaluation factors determining regional danger degree of debris flow.
Keywords:debris flow  projection pursuit cluster  danger degree  contribution rate  key factor
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