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基于模糊推理的粒子群优化算法
作者单位:;1.宁夏大学数学统计学院;2.北方民族大学信息与系统科学研究所
摘    要:针对无约束优化问题,提出了基于模糊推理的粒子群优化算法,该算法针对粒子群优化算法搜索能力的不足,先引入平均粒子,然后引入模糊推理来改进粒子群的速度更新公式,再利用模糊推理动态地改进算法惯性权重和速度更新公式的权重因子,再结合混沌扰动增加算法后期的局部搜索能力.数值试验采用12个测试函数并有5个算法进行对比,数值试验证明,改进算法的搜索能力有较大的提高.

关 键 词:粒子群优化  模糊推理  信息共享

Particle Swarm Optimization Algorithm Based on Fuzzy Reason
Institution:,School of Mathematics and Computer,Ningxia University,Research Institute of Information and System Computation Science,Beifang University of Nationalities
Abstract:It is well know that the standard PSO is unreliable to solve unrestraint problems with global optimization,due to the insufficient search ability nature of the PSO.In order to overcome the shortcoming,the particle swarm optimization algorithm based on fuzzy reason uses average particle,fuzzy reasoning to improve the speed of the particle swarm update formula.Fuzzy reasoning dynamically inertia weight and velocity updating formula of weight factor.Chaos disturbance increase algorithm local search ability in the late.A number of numerical examples which are used twelve trial functions have shown the present method is found to be ultra-accurate,capable of modeling global optimization.
Keywords:particle swarm optimization  Fuzzy reasoning  information sharing
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