Abstract
AbstractBased on the research results published in existing relevant references, the basic principles of the standard particle swarm optimization (PSO) algorithm are elaborated and analyzed. To the shortcomings of the standard particle swarm optimization algorithm such as the success rate, number of iterations, running time and the local optimum in the optimization process, a new kind of decay-curve inertia weight Particle Swarm Optimization Algorithm (CPSO) is presented and the astringency analysis is finished. The comparison between the CPSO algorithm and the standard PSO algorithm through the experiment a analysis show that, the CPSO algorithm is apparently better than the standard PSO algorithm both in the convergence speed an convergence precision.Keywordsdecay-curve inertia weighPSOconvergence performance
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