MAT之PSO：利用PSO实现对一元函数y = sin(10*pi*x) ./ x进行求解优化，找到最优个体适应度

MAT之PSO：利用PSO实现对一元函数y = sin(10*pi*x) ./ x进行求解优化，找到最优个体适应度

 

 

目录

输出结果

代码设计

---

 

 

 

 

输出结果

代码设计

x = 1:0.01:2; y = sin(10*pi*x) ./ x; figure plot(x, y) title('绘制目标函数曲线图—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)实现找到最优个体适应度—Jason niu','fontsize',12); xlabel('进化代数','fontsize',12);ylabel('适应度','fontsize',12);

 

 相关文章
PSO：利用PSO+ω参数实现对一元函数y = sin(10*pi*x) ./ x进行求解优化，找到最优个体适应度
 

《新程序员》：云原生和全面数字化实践50位技术专家共同创作，文字、视频、音频交互阅读

总结

以上是生活随笔为你收集整理的MAT之PSO：利用PSO实现对一元函数y = sin(10*pi*x) ./ x进行求解优化，找到最优个体适应度的全部内容，希望文章能够帮你解决所遇到的问题。

如果觉得生活随笔网站内容还不错，欢迎将生活随笔推荐给好友。