科研之友
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摘要
In particle swarm optimization, although falling into local optimums can be avoided by introducing the information of multi-optimum distribution state into the particle swarm movement, the performance of the algorithm is limited because the programming proportion factor of multi-optimum cannot be dynamically adjusted in the optimization process. A kind of fuzzy strategy based on double-variable and single-dimensional fuzzy control structure is proposed and used to the dynamic programming of particle swarm multi-optimum. Simulation results show that this kind of fuzzy multi-optimum programming mode has better general convergence performance than traditional PSO algorithm and the static multi-optimum programming mode.
- 出版日期2006
- 单位同济大学
