A Study of Acceleration Coefficients in Particle Swarm Optimization Algorithm Based on CPSO

Low convergence accuracy and the acceleration coefficient setting problem have always been the difficult and hot research points of particle swarm optimization algorithm. This paper introduces a composite particle swarm optimization CPSO based on the adaptive PSO and adaptive GA and applies CPSO in...

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Bibliographic Details
Published in2010 2nd International Conference on Information Engineering and Computer Science pp. 1 - 4
Main Authors Pu Sun, Hua Sun, Wenquan Feng, Qi Zhao, Hongbo Zhao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2010
Subjects
Acceleration
Accuracy
Algorithm design and analysis
Convergence
Optimization
Particle swarm optimization
Training
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Summary:Low convergence accuracy and the acceleration coefficient setting problem have always been the difficult and hot research points of particle swarm optimization algorithm. This paper introduces a composite particle swarm optimization CPSO based on the adaptive PSO and adaptive GA and applies CPSO in the BP network training of turbo-pump fault diagnosis. In addition, the classical test function Rastrigrin is performed to test the performance of CPSO. The simulation results show that CPSO has obvious advantages over other optimization algorithms in terms of convergence accuracy and the law of acceleration coefficient setting is summed up through the analysis of the simulation results of acceleration coefficient distribution.
ISBN:1424479398
9781424479399
ISSN:2156-7379
DOI:10.1109/ICIECS.2010.5677729