MAT之PSO：利用PSO實(shí)現(xiàn)對一元函數(shù)y = sin(10*pi*x) ./ x進(jìn)行求解優(yōu)化，找到最優(yōu)個(gè)體適應(yīng)度

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目錄

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代碼設(shè)計(jì)

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輸出結(jié)果

代碼設(shè)計(jì)

x = 1:0.01:2; y = sin(10*pi*x) ./ x; figure plot(x, y) title('繪制目標(biāo)函數(shù)曲線圖—Jason niu'); hold onc1 = 1.49445; c2 = 1.49445;maxgen = 50; sizepop = 10; Vmax = 0.5; Vmin = -0.5; popmax = 2; popmin = 1;for i = 1:sizepoppop(i,:) = (rands(1) + 1) / 2 + 1; V(i,:) = 0.5 * rands(1); fitness(i) = fun(pop(i,:)); end[bestfitness bestindex] = max(fitness); zbest = pop(bestindex,:); gbest = pop; fitnessgbest = fitness; fitnesszbest = bestfitness; for i = 1:maxgenfor j = 1:sizepopV(j,:) = V(j,:) + c1*rand*(gbest(j,:) - pop(j,:)) + c2*rand*(zbest - pop(j,:));V(j,find(V(j,:)>Vmax)) = Vmax; V(j,find(V(j,:)<Vmin)) = Vmin;pop(j,:) = pop(j,:) + V(j,:);pop(j,find(pop(j,:)>popmax)) = popmax; pop(j,find(pop(j,:)<popmin)) = popmin;fitness(j) = fun(pop(j,:)); endfor j = 1:sizepop if fitness(j) > fitnessgbest(j)gbest(j,:) = pop(j,:); fitnessgbest(j) = fitness(j);endif fitness(j) > fitnesszbestzbest = pop(j,:);fitnesszbest = fitness(j);endend yy(i) = fitnesszbest; end[fitnesszbest zbest] plot(zbest, fitnesszbest,'r*')figure plot(yy) title('PSO：PSO算法(快于GA算法)實(shí)現(xiàn)找到最優(yōu)個(gè)體適應(yīng)度—Jason niu','fontsize',12); xlabel('進(jìn)化代數(shù)','fontsize',12);ylabel('適應(yīng)度','fontsize',12);

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