Journal of Jilin University(Earth Science Edition) ›› 2016, Vol. 46 ›› Issue (4): 1168-1175.doi: 10.13278/j.cnki.jjuese.201604203

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

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

  1. 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)

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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

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