tic?%?計時器
%%?清空環境變量
clear
clc
%%?利用灰狼算法選擇最佳的SVM參數c和g
SearchAgents_no=20;?%?狼群數量，Number?of?search?agents
Max_iteration=100;?%?最大迭代次數，Maximum?numbef?of?iterations
dim=2;?%?此例需要優化兩個參數c和g，number?of?your?variables
lb=[0.010.01];?%?參數取值下界
ub=[100100];?%?參數取值上界
%?v?=?5;?%?SVM?Cross?Validation參數默認為5

%?initialize?alpha?beta?and?delta_pos
Alpha_pos=zeros（1dim）;?%?初始化Alpha狼的位置
Alpha_score=inf;?%?初始化Alpha狼的目標函數值，change?this?to?-inf?for?maximization?problems

Beta_pos=zeros（1dim）;?%?初始化Beta狼的位置
Beta_score=inf;?%?初始化Beta狼的目標函數值，change?this?to?-inf?for?maximization?problems

Delta_pos=zeros（1dim）;?%?初始化Delta狼的位置
Delta_score=inf;?%?初始化Delta狼的目標函數值，change?this?to?-inf?for?maximization?problems

%Initialize?the?positions?of?search?agents
Positions=initialization（SearchAgents_nodimublb）;

Convergence_curve=zeros（1Max_iteration）;

l=0;?%?Loop?counter循環計數器

%?Main?loop主循環
while?l????for?i=1:size（Positions1）??%?遍歷每個狼
???????flag=1;
???????%?Return?back?the?search?agents?that?go?beyond?the?boundaries?of?the?search?space
???????%?若搜索位置超過了搜索空間，需要重新回到搜索空間
????????Flag4ub=Positions（i:）>ub;
????????Flag4lb=Positions（i:）????????%?若狼的位置在最大值和最小值之間，則位置不需要調整，若超出最大值，最回到最大值邊界；
????????%?若超出最小值，最回答最小值邊界
????????Positions（i:）=（Positions（i:）.*（~（Flag4ub+Flag4lb）））+ub.*Flag4ub+lb.*Flag4lb;?%?~表示取反???????????
??????
??????
???????
???????if（conf（Positions（i1）Positions（i2）））%如不滿足約束條件
???????????flag=0;
???????end
???????if（flag==1）?%如滿足約束條件
???????????%?計算適應度函數值
????????????fitnessw=f（Positions（i1）Positions（i2））;
????????????fitness=fitnessw;?%?正求最小值，負求最大值

????????????%?Update?Alpha?Beta?and?Delta
????????????if?fitness????????????????Alpha_score=fitness;?%?則將Alpha狼的目標函數值更新為最優目標函數值，Update?alpha
????????????????Alpha_pos=Positions（i:）;?%?同時將Alpha狼的位置更新為最優位置
????????????end

????????????if?fitness>Alpha_score?&&?fitness????????????????Beta_score=fitness;?%?則將Beta狼的目標函數值更新為最優目標函數值，Update?beta
????????????????Beta_pos=Positions（i:）;?%?同時更新Beta狼的位置
????????????end

????????????if?fitness>Alpha_score?&&?fitness>Beta_score?&&?fitness????????????????Delta_score=fitness;?%?則將Delta狼的目標函數值更新為最優目標函數值，Update?delta
????????????????Delta_pos=Positions（i:）;?%?同時更新Delta狼的位置
????????????end
???????end

????end
????
????a=2*cos（l/Max_iteration*pi/2）;?%?對每一次迭代，計算相應的a值，a?decreases?linearly?fron?2?to?0
????
????%?Update?the?Position?of?search?agents?including?omegas
????for?i=1:size（Positions1）?%?遍歷每個狼
????????for?j=1:size（Positions2）?%?遍歷每個維度
????????????
????????????%?包圍獵物，位置更新
????????????
????????????r1=rand（）;?%?r1?is?a?random?number?in?[01]
????????????r2=rand（）;?%?r2?is?a?random?number?in?[01]
????????????
????????????A1=2*a*r1-a;?%?計算系數A，Equation?（3.3）
????????????C1=2*r2;?%?計算系數C，Equation?（3.4）
????????????
????????????%?Alpha

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????4789??2019-11-08?12:08??JGWO\CalGWO.m
?????文件????????1779??2019-11-08?12:04??JGWO\Calolot.m
?????文件?????1753133??2016-09-08?10:07??JGWO\GWO_finalVersion.pdf
?????文件?????????171??2019-11-07?11:31??JGWO\conf.m
?????文件?????????101??2019-11-07?11:32??JGWO\f.m
?????文件????????2091??2019-11-08?12:04??JGWO\initialization.m
?????目錄???????????0??2019-11-08?12:04??JGWO\