Factor Identification for Regional Danger Degree of Debris Flow

SU Peng-cheng; NI Chang-jian; KONG Ji-ming; WANG Yan-chun

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Factor Identification for Regional Danger Degree of Debris Flow

- Factor Identification for Regional Danger Degree of Debris Flow
- Bulletin of Soiland Water Conservation Vol. 28, Issue 1, Pages: 128-132(2009)
- 作者机构：
  
  1. 中国科学院山地灾害与地表过程重点实验室,四川,成都,610041
  2. 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
  3. 成都信息工程学院,四川,成都,610225
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2009
- 稿件说明：
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SU Peng-cheng, NI Chang-jian, KONG Ji-ming, et al. Factor Identification for Regional Danger Degree of Debris Flow[J]. Bulletin of Soiland Water Conservation, 2009, 28(1): 128-132.
DOI：

SU Peng-cheng, NI Chang-jian, KONG Ji-ming, et al. Factor Identification for Regional Danger Degree of Debris Flow[J]. Bulletin of Soiland Water Conservation, 2009, 28(1): 128-132. DOI：

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。

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.

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