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Chaos Particle Swarm Optimization Algorithm for Optimization Problems.

Authors :
Liu, Wenbin
Luo, Nengsheng
Pan, Guo
Ouyang, Aijia
Source :
International Journal of Pattern Recognition & Artificial Intelligence. Nov2018, Vol. 32 Issue 11, pN.PAG-N.PAG. 18p.
Publication Year :
2018

Abstract

A chaos particle swarm optimization (CPSO) algorithm based on the chaos operator (CS) is proposed for global optimization problems and parameter inversion of the nonlinear sun shadow model in our study. The CPSO algorithm combines the local search ability of CS and the global search ability of PSO algorithm. The CPSO algorithm can not only solve the global optimization problems effectively, but also address the parameter inversion problems of the date of sun shadow model location successfully. The results of numerical experiment and simulation experiment show that the CPSO algorithm has higher accuracy and faster convergence than the-state-of-the-art techniques. It can effectively improve the computing accuracy and computing efficiency of the global optimization problems, and also provide a novel method to solve the problems of integer parameter inversion in real life. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02180014
Volume :
32
Issue :
11
Database :
Academic Search Index
Journal :
International Journal of Pattern Recognition & Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
130870861
Full Text :
https://doi.org/10.1142/S021800141859019X