PSO.rar_GA PSO算法_PSO_pso迭代_迭代搜索_迭代搜索算法

clear clc global popsize %%粒子群个数 popsize=100; global dimsize %%变量个数 dimsize=10; global a0min %%a0下限 a0min=-1e-10; global a0max %%a0上限 a0max=1e-10; global a1min %%a1下限 a1min=1e-10; global a1max %%a1上限 a1max=9e-10; global dmin %%d下限 dmin=200; global dmax %%d上限 dmax=300; global gmin %%g下限 gmin=-0.2; global gmax %%g上限 gmax=0.8; global va0min %%a0下限 va0min=-1e-10; global va0max %%a0上限 va0max=1e-10; global va1min %%a1下限 va1min=1e-10; global va1max %%a1上限 va1max=9e-10; global vdmin %%d下限 vdmin=200; global vdmax %%d上限 vdmax=300; global vgmin %%g下限 vgmin=-0.2; global vgmax %%g上限 vgmax=0.8; global wcmax %% wcmax=0.9; global wcmin %% wcmin=0.1; global c1 global c2 c1=2; c2=2; global maxgeneration %%迭代总次数 maxgeneration=100; global generation global PBEST global GBEST global PVALUER global GVALUER global YY YY=[-0.54081-0.60692i,0.012149 + 0.68679i,0.11882 - 0.19483i,0.13601 - 0.34158i,-0.4657 + 0.35149i,0.57219 + 0.084515i,-0.30602 - 0.45357i,-0.12448 + 0.4733i,0.28253 - 0.22736i,-0.041232 - 0.046053i,-0.27818 + 0.10149i,0.35255 + 0.10889i,-0.15708-0.33035i,-0.12981+0.30804i,0.27992-0.10334i,-0.16859-0.046979i,-0.074748+0.027345i,0.18405+0.1087i,-0.06962-0.22639i,-0.11754+0.19898i,0.20472-0.035646i,-0.14713-0.09783i,0.015134 + 0.072464i,0.065154+0.05626i,-0.01676-0.14516i,-0.096746+0.11933i,0.14494-0.0074938i,-0.089348-0.095349i,0.0039871+0.09879i,0.030279-0.0085858i]; global f; f=1000000:1000000:30000000; generation=1; %%第一次 pop=initpop(popsize); %%初始化 [pbest,gbest,objvalue,gvaluer]=calobjvalue(pop);%%calobjvalue函数的功能是计算目标函数的适应度 PBEST=pbest; GBEST=gbest; PVALUER=objvalue; GVALUER=gvaluer; %[pbest,gbest,pvaluer,objvaluetemp]=regulate(pop,pbest,gbest,objvalue);%%粒子在进化过程中依据其适应度,调节个体最好位置Pbest和群体最好位置best pop=renew(pop,PBEST,GBEST); %%%对粒子的速度和位置进行进化 for generation=2:maxgeneration %%迭代次数 [pbest,gbest,objvalue]=calobjvalue(pop);%%calobjvalue函数的功能是计算目标函数的适应度 for n=1:popsize if(objvalue(n,1)<PVALUER(n,1)) PVALUER(n,1)=objvalue(n,1); PBEST(n,1:dimsize)=pbest(n,1:dimsize) end end [GVALUER,m]=min(PVALUER); GVALUER GBEST=PBEST(m,1:dimsize) %[pbest,gbest,pvaluer,objvaluetemp]=regulate(pop,PBEST,GBEST,objvalue);%%粒子在进化过程中依据其适应度,调节个体最好位置Pbest和群体最好位置best pop=renew(pop,PBEST,GBEST); %%%对粒子的速度和位置进行进化 end GBEST GVALUER k=0.95; a0=GBEST(1,1);a1=GBEST(1,2); g=[GBEST(1,7),GBEST(1,8),GBEST(1,9),GBEST(1,10)]; d=[GBEST(1,3),GBEST(1,4),GBEST(1,5),GBEST(1,6)]; c=1.5*10^8; HH=0; for i=1:4 H=g(1,i)*exp(-(a0+a1*f.^k)*d(1,i)-j*2*pi*f.*d(1,i)/c); %H=g(1,i)*exp(-(a0+a1*f.^k)*d(1,i)).*exp(-j*2*3.14*f*d(1,i)/c); HH=HH+H; end plot(f,HH,'r-',f,YY,'g-'); grid on; LEGEND('粒子群算法','实测值');