Insulation Optimization System of Mixed Gas based on Intelligent Particle Swarm Optimization

Abstract

Particle swarm optimization (PSO) is an intelligent evolutionary method, which is widely used to search the global optimal solution. However, in the early stage of the algorithm, the rapid flight of particle swarm to the current optimal solution may lead to premature convergence, while in the later stage of the algorithm, the convergence of most particles will lead to the decrease of particle swarm velocity. In this paper, the advantages and principles of IPSOA are discussed, and the insulation problem of mixed gas is discussed. By comparing the standard PSOA with the improved PSOA, the results show that the calculation result of the improved PSOA is close to the optimal value of the function itself, which proves that the improved PSOA has better optimization ability.