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A study of acceleration coefficients in particle swarm optimization algorithm based on CPSO

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2nd International Conference on Information Engineering and Computer Science - Proceedings, ICIECS 2010
DOIs
StatePublished - 2010
Event2nd International Conference on Information Engineering and Computer Science, ICIECS 2010 - Wuhan, China
Duration: 25 Dec 201026 Dec 2010

Publication series

Name2nd International Conference on Information Engineering and Computer Science - Proceedings, ICIECS 2010

Conference

Conference2nd International Conference on Information Engineering and Computer Science, ICIECS 2010
Country/TerritoryChina
CityWuhan
Period25/12/1026/12/10

Keywords

  • Acceleration coefficients
  • Adaptive genetic algorithm
  • Adaptive particle swarm optimization algorithm
  • BP network
  • Composite particle swarm optimization algorithm

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