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 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.

[1]  Zhang Yu,et al.  Multi-fault diagnosis for turbo-pump based on neural network , 2003 .

[2]  Lalit M. Patnaik,et al.  Adaptive probabilities of crossover and mutation in genetic algorithms , 1994, IEEE Trans. Syst. Man Cybern..

[3]  Saman K. Halgamuge,et al.  Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients , 2004, IEEE Transactions on Evolutionary Computation.

[4]  Zhijun Chen.  Optimization of Neural Network Based on Improved Genetic Algorithm , 2009, 2009 International Conference on Computational Intelligence and Software Engineering.

[5]  D.H. Werner,et al.  Particle swarm optimization versus genetic algorithms for phased array synthesis , 2004, IEEE Transactions on Antennas and Propagation.

[6]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[7]  Russell C. Eberhart,et al.  Guest Editorial Special Issue on Particle Swarm Optimization , 2004, IEEE Trans. Evol. Comput..

[8]  T. Krink,et al.  Particle swarm optimisation with spatial particle extension , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[9]  LI Rong-jun.  Experimental Analysis of Acceleration Coefficient in Particle Swarm Optimization Algorithm , 2010 .