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

Abstract

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

CLC Number:

P642.23

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

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