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parallel-asynchronous-pso_05

于 2011-04-25 发布文件大小:165KB

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下载积分: 1 下载次数: 7

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包括：用基本粒子群算法求解无约束优化问题，用带压缩因子的粒子群算法求解无约束优化问题，用线性递减权重粒子群优化算法求解无约束优化问题，用自适应权重粒子群优化算法求解无约束优化问题，用随机权重粒子群优化算法求解无约束优化问题，用学习因子同步变化的粒子群优化算法求解无约束优化问题，用学习因子异步变化的粒子群优化算法求解无约束优化问题，用二阶粒子群优化算法求解无约束优化问题，用二阶振荡粒子群优化算法求解无约束优化问题(Include: using the particle swarm algorithm for unconstrained optimization problems, with compression factor of particle swarm algorithm for solving unconstrained optimization problem with linear decreasing weight particle swarm optimization for unconstrained optimization problems, an adaptive weight particle swarm optimization unconstrained optimization problems, random weight particle swarm optimization algorithm for unconstrained optimization problems, with the learning factor synchronous change of particle swarm optimization algorithm for unconstrained optimization problems, with the learning factor asynchronous changes in particle swarm optimization algorithm for solving unconstrained optimization problem , with the second particle swarm optimization for unconstrained optimization problems, with the second-order oscillating particle swarm optimization algorithm for unconstrained optimization problem)

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用MATLAB编写的离散模糊控制程序，结合本程序，我相信能能更快更好的理解模糊控制算法。算法在MATLAB Version: 7.14.0.739 (R2012a)运行无误。 function [FCU_T1,FCU_T2,FCU_T3,FCU_T4]=fuzzy_table(Me,Mec,Mu,UC) Me 隶属度表1 Mec 隶属度表2 Mu 隶属度表3 UC 模糊规则 FCU_T1 重心加权法，输出精确值 FCU_T2 重心加权法，输出离散值 FCU_T3 重心加权法（对隶属度平方），输出离散值 FCU_T4 最大隶属度法 function [R,n,nE,nEC,nU,nfe,nfec,nfu]=fuzzy_relation(Me,Mec,Mu,UC) Me 隶属度表1 Mec 隶属度表2 Mu 隶属度表3 UC 模糊规则 R 表示全体规则构成的模糊关系 n=nfe×nfec nE 模糊变量E的语言值个数 nEC 表示模糊变量EC的语言值个数 nU 表示模糊变量U的语言值个数 nfe 表示E的等级量个数,示例1中其论域为{-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6} nfec 表示EC的等级量个数,示例1中其论域为{-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6} nfu 表示U的等级量个数,示例1中其论域为{-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7} Me 表示E的隶属度表 Mec 表示EC的隶属度表 Mu表示U的隶属度表 UC表示规则表(fuzzy control algorithm（matlab program）)

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