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改進型粒子群PSO優(yōu)化算法MATLAB代碼,基于權(quán)重改進速度,已封裝為函數(shù)

資源截圖

代碼片段和文件信息

function?[xminfmin]?=?PSO(fitnessNc1c2wmaxwminMD)?%?自適應(yīng)粒子群
%?fitness?適應(yīng)度函數(shù),也叫目標(biāo)函數(shù)
%?N?粒子個數(shù)
%?c1?學(xué)習(xí)因子1
%?c2?學(xué)習(xí)因子2
%?wmax?慣性權(quán)重最大值
%?wmin?慣性權(quán)重最小值
%?M?最大迭代次數(shù)
%?D?搜索空間維數(shù),數(shù)據(jù)(粒子)維數(shù)
%?xmin?目標(biāo)函數(shù)最小時的自變量x(粒子)
%?fmin?目標(biāo)函數(shù)最小值
%%%%%%?初始化種群個體,限定位置和速度?%%%%%%%
x?=?rand(ND);
v?=?rand(ND);
%%%%%%?初始化個體最優(yōu)位置及其最優(yōu)值(初始化各個粒子適應(yīng)度的值)?%%%%%%
for?i?=?1:N
????p(i:)?=?x(i:);
????p(i)?=?fitness(x(i:));
end
%%%%%%?初始化全局最優(yōu)位置及其最優(yōu)值(假設(shè)最后一個粒子為最優(yōu))?%%%%%%
pg(N:)?=?x(N:);
pg(i)?=?fitness(x(N:));
for?i?=?1:N
????if?fitness(x(i:))?????????pg(i:)?=?x(i:);
????????pg(i)?=?fitness(pg);
????end
end
%%%%%%?開始主循環(huán)?%%%%%%%
for?t?=?1:M
????%%%%%%?求目標(biāo)函數(shù)最小值、平均值,更新權(quán)重?%%%%%%
????for?j?=?1:N
????????fv(j)?=?fitness(x(j:));
????end
????favg?=?sum(fv)/N;
????fmin?=?min(fv);
????for?j?=?1:N
????????if?fv?<=?favg
????????????w?=?wmin?-?(wmax?-?wmin)?*?(fv?-?favg)/(favg?-?fmin);
????????else
????????????w?=?wmax;
????????end
????end
????%%%%%%?更新位置和速度(兩個公式)?%%%%%%
????for?i?=?1:N
????????v(i:)?=?w?*?v(i:)?+?c1?*?rand?*?(p(i:)?-?x(i:))?+?c2?*?rand?*?(pg(i:)?-x(i:));
????????x(i:)?=?x(i:)?+?v(i:);
????????%%%%%%?更新個體最優(yōu)位置?%%%%%%
????????if?fitness(x(i:))?????????p(i)?=?fitness(x(i:));
????????p(i:)?=?x(i:);
????????end
????????%%%%%%?更新全局最優(yōu)位置?%%%%%%
????????if?p(i)?????????pg(i:)?=?x(i:);
????????pg(i)?=?fitness(pg);
????????end
????end
end
xmin?=?pg(i:);
fmin?=?pg(i);

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????1667??2018-06-22?12:01??PSO_adaptation.m

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