PSO_GA_RBF.rar_5BB_RBF_ga-rbf _pso RBF MATLAB_rbf pso

%用粒子群算法优化回声神经网络ESN网络权值 clear all close all G =100; %迭代次数 n = 12; %粒子维数 m = 20; %种群规模 w = 0.1; %算法参数 c1 = 2; %算法参数 c2 = 2; %算法参数 %取粒子的取值范围 for i = 1:3 MinX(i) = 0.1*ones(1); MaxX(i) = 3*ones(1); end for i = 4:1:9 MinX(i) = -3*ones(1); MaxX(i) = 3*ones(1); end for i = 10:1:12 MinX(i) = -ones(1); MaxX(i) = ones(1); end %初始化种群pop pop = rands(m,n); for i = 1:m for j = 1:3 if pop(i,j) < MinX(j) pop(i,j) = MinX(j); end if pop(i,j) > MaxX(j) pop(i,j) = MaxX(j); end end for j = 4:9 if pop(i,j) < MinX(j) pop(i,j) = MinX(j); end if pop(i,j) > MaxX(j) pop(i,j) = MaxX(j); end end for j = 10:12 if pop(i,j) < MinX(j) pop(i,j) = MinX(j); end if pop(i,j) > MaxX(j) pop(i,j) = MaxX(j); end end end %初始化粒子速度 V = 0.1*rands(m,n); BsJ = 0; %根据初始化的种群计算个体好坏,找出群体最优和个体最优 for s = 1:m indivi = pop(s,:); %抽出个体 [indivi,BsJ] = fitness(indivi,BsJ); %求出每个粒子对应的误差 Error(s) = BsJ; end [OderEr,IndexEr] = sort(Error); %对误差进行排序 Error; Errorleast = OderEr(1); %求出最小误差 for i = 1:m if Errorleast == Error(i) gbest = pop(i,:); %找出最小误差对应的个体极值gbest(指的是个体) break; end end ibest = pop; %把初始化的种群作为群体极值ibest %循环开始 for kg = 1:G kg for s = 1:m; %个体有4%的变异概率 for j = 1:n for i = 1:m if rand(1)<0.04 pop(i,j) = rands(1); %对个体pop(i,j)进行变异 end end end %r1,r2为粒子群算法参数 r1 = rand(1); r2 = rand(1); % 速度更新 V(s,:) = w*V(s,:) + c1*r1*(ibest(s,:)-pop(s,:)) + c2*r2*(gbest-pop(s,:)); %个体更新 pop(s,:) = pop(s,:) + 0.3*V(s,:); for j = 1:3 if pop(s,j) < MinX(j) pop(s,j) = MinX(j); end if pop(s,j) > MaxX(j) pop(s,j) = MaxX(j); end end for j = 4:9 if pop(s,j) < MinX(j) pop(s,j) = MinX(j); end if pop(s,j) > MaxX(j) pop(s,j) = MaxX(j); end end for j = 10:12 if pop(s,j) < MinX(j) pop(s,j) = MinX(j); end if pop(s,j) > MaxX(j) pop(s,j) = MaxX(j); end end %求更新后的每个个体误差，可看成适应度值 [pop(s,:),BsJ] = fitness(pop(s,:),BsJ); error(s) = BsJ; %根据适应度值对个体最优和群体最优进行更新 if error(s)<Error(s) ibest(s,:) = pop(s,:); Error(s) = error(s); end if error(s)<Errorleast gbest = pop(s,:); Errorleast = error(s); end end Best(kg) = Errorleast; end plot(Best); title('遗传算法优化RBF网络权值中最小误差进化过程') xlabel('进化次数'); ylabel('最小误差'); save pfile1 gbest;