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.