A fuzzy clustering iterative model using chaotic differential evolution algorithm for evaluating flood disaster

被引:43
作者
He, Yaoyao [1 ,2 ,3 ]
Zhou, Jianzhong [3 ]
Kou, Pangao [3 ]
Lu, Ning [3 ,4 ]
Zou, Qiang [3 ]
机构
[1] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
[2] Minist Educ, Key Lab Proc Optimizat & Intelligent Decis Making, Hefei, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China
[4] Wuhan Univ Technol, Sch Automat, Wuhan, Hubei, Peoples R China
基金
中国博士后科学基金;
关键词
Flood disaster evaluation; Evolutionary computation; Differential evolution algorithm; Fuzzy clustering; Chaotic map; OPTIMIZATION; PATTERN;
D O I
10.1016/j.eswa.2011.02.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Flood disaster is a kind of frequent natural hazards. The objective of flood disaster evaluation is to establish hazard assessment model for managing flood and preventing disaster. Base on the chaotic optimization theory, this paper proposes a chaotic differential evolution algorithm to solve a fuzzy clustering iterative model for evaluating flood disaster. By using improved logistic chaotic map and penalty function, the objective function can be solved more perfectly. Two practical flood disaster cases have been taken into account so as to test the effect of novel hybrid method. Simulation results and comparisons show that the chaotic differential evolution algorithm is competitive and stable in performance with simple differential evolution and other optimization approaches presented in literatures. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:10060 / 10065
页数:6
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