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《Journal of Baoding University》 2008-04
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Using PSO Algorithm to Solve Nonlinear Multiregression Based on Generalized Choquet Integrals

XIAO Tao1,2,HUANG Dong-mei2,ZHANG Ning1,3(1.College of Mathematics and Computer,Hebei University,Baoding 071002,China;2.College of Science,Agricultural University of Hebei,Baoding 071001,China;3.Key Lab.for Machine Learning and Computational Intelligence,Hebei University,Baoding 071002,China)  
Multiregression is one of the most common approaches used in data mining.The crux of using a nonlinear multiregression model is how to optimally determine the unknown regression parameters that include values of the fuzzy measures.Considering the high complexity and low convergence speed of gennetic algorithm in solving nonlinear multiregression,we use PSO(Particle Swarm Optimization) to solve nonlinear multiregression based on generalized Choquet integrals.Comparative experiments are conducted on both simulated and real data sets,and the results show that PSO can converge faster and obtain optimal solution than genetic algorithm for solving nonlinear multiregression.
【Fund】: 河北省自然科学基金(F2008000635);; 河北省教育厅首批百名优秀人才支持计划资助项目;; 河北省科学技术研究与发展指导计划资助项目(06213548);; 河北农业大学非生命学科与新兴学科科研发展基金(200809)
【CateGory Index】: O212.1
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