泥石流危险性评价:模糊c均值聚类-支持向量机法

doi:10.13278/j.cnki.jjuese.201604203

吉林大学学报(地球科学版) ›› 2016, Vol. 46 ›› Issue (4): 1168-1175.doi: 10.13278/j.cnki.jjuese.201604203

泥石流危险性评价:模糊c均值聚类-支持向量机法

王常明¹, 田书文¹, 王翊虹², 阮云凯¹, 丁桂伶²

1. 吉林大学建设工程学院, 长春 130026;
2. 北京市地质研究所, 北京 100111

收稿日期:2016-03-05 出版日期:2016-07-26 发布日期:2016-07-26
通讯作者: 田书文(1988),男,博士研究生,主要从事地质灾害防治及工程地质方面的研究,E-mail:597758449@qq.com E-mail:597758449@qq.com
作者简介:王常明(1966),男,教授,博士生导师,主要从事土力学及地质灾害方面的研究,E-mail:wangcm@jlu.edu.cn
基金资助:
国家自然科学基金面上项目（41572257，40972171）；北京市科技计划项目（Z141100003614052）

Risk Assessment of Debris Flow: A Method of SVM Based on FCM

Wang Changming¹, Tian Shuwen¹, Wang Yihong², Ruan Yunkai¹, Ding Guiling²

1. College of Construction Engineering, Jilin University, Changchun 130026, China;
2. Beijing Geology Institute, Beijing 100011, Chana

Received:2016-03-05 Online:2016-07-26 Published:2016-07-26
Supported by:
Supported by National Science Foundation of China (41572257, 40972171)and Beijing Science and Technology Project(Z141100003614052)

摘要/Abstract

摘要：

泥石流是一种能够造成灾难性后果的严重自然灾害，准确可靠的泥石流危险性评价对于其预警及防治工作来说至关重要。泥石流的危险性评价方法有很多，模糊c均值聚类（FCM）方法是其中一种应用广泛的分类方法；相比其他方法而言，其无需主观确定边界，并且能以各级隶属度矩阵为输出结果，方便应用。支持向量机（SVM）是基于结构风险最小化为目标的机器学习理论，以支持向量为算法支撑，具有一定的鲁棒性，并且适合在小样本条件下进行分类。本文选用FCM和SVM联合的方法，开展泥石流危险性的评价；对北京房山区南窖沟泥石流危险性进行分析，并对比其他评价方法所得结果，证明本文提出的评价方法具有较好的效果。

关键词: 泥石流, 危险性分类, 模糊c均值聚类, 支持向量机

Abstract:

Debris flow is a kind of nature hazard which can produce serious consequences, and the accuracy of debris flow risk classification is important for the early warning and disaster prevention.Now there are a lot of algorithms used to evaluate the risk of debris flow. Fuzzy c means (FCM) algorithm is one of the widely used algorithms. Compared with general classification method, FCM does not need to determine risk boundaries artificially, and it outputs membership degree matrix for each risk degree. Support vector machine (SVM) is a machine algorithm based on structure risk minimization. It establishes classification model by support vectors and has better Robustness. It is well applied to small samples. In this paper, the SVM method based on FCM is used for debris flow risk evaluation, which gets a good classification performance.

Key words: debris-flow, risk classification, FCM, SVM

中图分类号:

P642.23

王常明, 田书文, 王翊虹, 阮云凯, 丁桂伶. 泥石流危险性评价:模糊c均值聚类-支持向量机法[J]. 吉林大学学报(地球科学版), 2016, 46(4): 1168-1175.

Wang Changming, Tian Shuwen, Wang Yihong, Ruan Yunkai, Ding Guiling. Risk Assessment of Debris Flow: A Method of SVM Based on FCM[J]. Journal of Jilin University(Earth Science Edition), 2016, 46(4): 1168-1175.

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泥石流危险性评价:模糊c均值聚类-支持向量机法

Risk Assessment of Debris Flow: A Method of SVM Based on FCM

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