MAT之PSO：利用PSO算法優化二元函數，尋找最優個體適應度

?

?

目錄

實現結果

設計代碼

---

?

?

?

實現結果

?

設計代碼

figure [x,y] = meshgrid(-5:0.1:5,-5:0.1:5); z = x.^2 + y.^2 - 10*cos(2*pi*x) - 10*cos(2*pi*y) + 20; mesh(x,y,z) hold onc1 = 1.49445; c2 = 1.49445;maxgen = 1000; sizepop = 100; Vmax = 1; Vmin = -1; popmax = 5; popmin = -5;for i = 1:sizepoppop(i,:) = 5*rands(1,2); V(i,:) = rands(1,2); 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:sizepop V(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] plot3(zbest(1), zbest(2), fitnesszbest,'ro','linewidth',1.5) title('粒子群算法：繪制的目標函數三維網格圖,紅圈為最優點—Jason niu')figure plot(yy) title('PSO：利用粒子群算法實現對目標函數尋找最優個體適應度—Jason niu','fontsize',12); xlabel('進化代數','fontsize',12);ylabel('適應度','fontsize',12);

?

?相關文章
PSO：利用PSO算法優化二元函數，尋找最優個體適應度

?

?

總結

以上是生活随笔為你收集整理的MAT之PSO：利用PSO算法优化二元函数，寻找最优个体适应度的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。