蟻群聚類算法matlab源代碼

functionQ=FINDabc(A)%給定B1,B2兩點(diǎn)坐標(biāo)計(jì)算平面參數(shù)a,b,cv=1e-3*[1111];r=1.3;l=0;K=6;a=RAND;a=RESHAP_MAX(A,a,K);while(sum(STAND(A,a(K,:))>v)?=0)l=0;[Q,w]=REF(a,r,K);while((?D_ZONE1(Q))l(COMP(A,Q)>=COMP(A,a(K,:))))[Q,w]=REF(a,w,K);if(w<=epsA12)a(K,:)=[];K=K-1;l=1;endif(l==1)break;endendif(~l)a(K,:)=Q;endif(K<=1)a=FINDabc(A);break;enda=RESHAP_MAX(A,a,K);endif(K<=1)Q=a(1,:);elseQ=sum(a)./K;end11functionP=TEXT(i)%對(duì)i組[a,b,c]檢驗(yàn)，返回[a,b,c,a',b',c']j=1;while(j<=i)A(1,1:2)=CREAT_RAND12;A(1,3)=CREAT_RAND3;if(D_ZONE(A(1,:))==1)b(j,:)=A(1,:);j=j+1;endendforj=1:ic(j,:)=Fx(b(j,:));d(j,:)=FINDabc(c(j,:));e(j,:)=(d(j,:)-b(j,:))./b(j,:);endP=[b,d,e];plot(e(:,1),'b--o');holdon;plot(e(:,2),'g-.x');plot(e(:,3),'r:+');functionp=recognize(i)%分辨率的影響j=1;while(j<=i)a(1,1:2)=CREAT_RAND12();a(1,3)=CREAT_RAND3();if(D_ZONE(a(1,:)))b(j,:)=a(1,:);j=j+1;endendforj=1:ic(j,:)=Fx(b(j,:));e(j,:)=1e-4*round(1e4*c(j,:));endforj=1:if(j,1:3)=FINDabc(e(j,:));endhl=(b-f)./b;forj=1:3h(:,j)=sum(abs(hl(:,j)))/i*ones(i,1);endplot(h(:,1),'--r');holdon;plot(h(:,2),'-y');plot(h(:,3),':k');p=h;12functionQ_C12=CREAT_RAND12()if(y_C12<=0.5)Q_C12(1)=0.0017*rand(1);elseQ_C12(1)=-0.0017*rand(1);endy_C12=rand(1);if(y_C12<=0.5)Q_C12(2)=0.0017*rand(1);elseQ_C12(2)=-0.0017*rand(1);EndfunctionQ_C=CREAT_RAND3()y_C=rand(1);if(y_C<=0.5)Q_C=3*1e-6*rand(1);elseQ_C=-3*1e-6*rand(1);endfunctiony=D_ZONE(Q_D)p=pi/180/10;a=Q_D(1);b=Q_D(2);c=Q_D(3);if((abs(c)<3*1e-6)&((aA2+bA2)<(1/cos(p))A2-1))y=1;elsey=0;endfunctiony=D_ZONE1(Q_D)p=pi/180/10;a=Q_D(1);b=Q_D(2);c=Q_D(3);if((abs(c)v=3*1e-6)&((aA2+bA2)v=4*(1/cos(p))A2-1))y=1;elsey=0;end13functionQ_F=Fx(x)D=-7*1e-1;h=3*1e-1;B=-0.253;F=-0.259;a=x(1);b=x(2);c=x(3);s3=2*(c+D)/(1+aA2+bA2);s2=-b*s3;s1=-a*s3;c13=(c+D)/(1-b*B);c12=B*c13;c23=(c+D)/(1-b*F);c22=F*c23;B11=(h-s3)*(-s1)/(c13-s3)+s1;B12=(h-s3)*(c12-s2)/(c13-s3)+s2;B21=(h-s3)*(-s1)/(c23-s3)+s1;B22=(h-s3)*(c22-s2)/(c23-s3)+s2;Q_F=[B11,B12,B21,B22];functionA=RAND()i=1;while(i<=6)A(i,1:2)=CREAT_RAND12;A(i,3)=CREAT_RAND3;if(D_ZONE(A(i,:))==1)i=i+1;endendfunction[Q,w]=REF(C,r,k)B=C(k,:);C(k,:)=[];A=zeros(1,3);fori=1:(k-1)A=A+C(i,:);endifk>=2A=A/(k-1);endQ=A+r*(A-B);w=r/2;end14functionQ_M=RESHAP_MAX(B,A,K)p=0;a=0;fori=1:Kx(i)=COMP(B,A(i,:));endj=max(x);fori=1:Kifx(i)==j,p=i;endenda=A(p,:);A(p,:)=A(K,:);A(K,:)=a;Q_M=A;Endfunctionw=STAND(A,R)D=-7*1e-1;h=3*1e-1;B=-.253;F=-.259;a=R(1);b=R(2);c=R(3);B11=A(1);B12=A(2);B21=A(3);B22=A(4);s3=2*(c+D)/(1+aA2+bA2);s2=-b*s3;s1=-a*s3;c13=(c+D)/(1-b*B);c12=B*c13;c23=(c+D)/(1-b*F);c22=F*c23;F11=(h-s3)*(-s1)/(c13-s3)+s1;F12=(h-s3)*(c12-s2)/(c13-s3)+s2;F21=(h-s3)*(-s1)/(c23-s3)+s1;F22=(h-s3)*(c22-s2)/(c23-s3)+s2;w(1)=abs(B11-F11);w(2)=abs(B12-F12);w(3)=abs(B21-F21);w(4)=abs(B22-F22);function[R_best,L_best,L_ave,Shortest_Route,Shortest_Length]=ACATSP(C,NC_max,m,Alpha,Beta,Rho,Q)%%=====================================================%%ACATSP.m%%AntColonyAlgorithmforTravelingSalesmanProblem%%ChengAihua,PLAInformationEngineeringUniversity,ZhengZhou,China%%Email:aihuacheng@%%Allrightsreserved%% %%主要符號(hào)說明%%Cn個(gè)城市的坐標(biāo)，nx2的矩陣%%NC_max最大迭代次數(shù)%%m螞蟻個(gè)數(shù)%%Alpha表征信息素重要程度的參數(shù)%%Beta表征啟發(fā)式因子重要程度的參數(shù)%%Rho信息素蒸發(fā)系數(shù)%%Q信息素增加強(qiáng)度系數(shù)%%R_best各代最佳路線%%L_best各代最佳路線的長(zhǎng)度%%=====================================================%%第一步：變量初始化n=size(C,1);%n表示問題的規(guī)模(城市個(gè)數(shù))D=zeros(n,n);%D表示完全圖的賦權(quán)鄰接矩陣fori=1:nforj=1:nifi~=jD(i,j)=((C(i,1)-C(j,1))A2+(C(i,2)-C(j,2))A2)y.5;elseD(i,j)=eps;endD(j,i)=D(i,j);endendEta=1./D;%Eta為啟發(fā)因子，這里設(shè)為距離的倒數(shù)Tau=ones(n,n);%Tau為信息素矩陣Tabu=zeros(m,n);%存儲(chǔ)并記錄路徑的生成NC=1;%迭代計(jì)數(shù)器R_best=zeros(NC_max,n);%各代最佳路線L_best=inf.*ones(NC_max,1);%各代最佳路線的長(zhǎng)度L_ave=zeros(NC_max,1);%各代路線的平均長(zhǎng)度whileNC<=NC_max%停止條件之一：達(dá)到最大迭代次數(shù)%%第二步：將m只螞蟻放到n個(gè)城市上Randpos=[];fori=1:(ceil(m/n))Randpos=[Randpos,randperm(n)];endTabu(:,1)=(Randpos(1,1:m))';%%第三步：m只螞蟻按概率函數(shù)選擇下一座城市，完成各自的周游forj=2:nfori=1:mvisited=Tabu(i,1:(j-1));%已訪問的城市J=zeros(1,(n-j+1));%待訪問的城市P=J;%待訪問城市的選擇概率分布Jc=1;fork=1:niflength(find(visited==k))==0J(Jc)=k;Jc=Jc+1;endend%下面計(jì)算待選城市的概率分布fork=1:length(J)P(k)=(Tau(visited(end),J(k))AAlpha)*(Eta(visited(end),J(k))ABeta);endP=P/(sum(P));%按概率原則選取下一個(gè)城市Pcum=cumsum(P);Select=find(Pcum>=rand);to_visit=J(Select(1));Tabu(i,j)=to_visit;endendifNC>=2Tabu(1,:)=R_best(NC-1,:);end%%第四步：記錄本次迭代最佳路線L=zeros(m,1);fori=1:mR=Tabu(i,:);forj=1:(n-1)L(i)=L(i)+D(R(j),R(j+1));endL(i)=L(i)+D(R(1),R(n));endL_best(NC)=min(L);pos=find(L==L_best(NC));R_best(NC,:)=Tabu(pos(1),:);L_ave(NC)=mean(L);NC=NC+1%%第五步：更新信息素Delta_Tau=zeros(n,n);fori=1:mforj=1:(n-1)Delta_Tau(Tabu(i,j),Tabu(i,j+1))=Delta_Tau(Tabu(i,j),Tabu(i,j+1))+Q/L(i);endDelta_Tau(Tabu(i,n),Tabu(i,1))=Delta_Tau(Tabu(i,n),Tabu(i,1))+Q/L(i);endTau=(1-Rho).*Tau+Delta_Tau;%%第六步：禁忌表清零Tabu=zeros(m,n);end%%第七步：輸出結(jié)果Pos=find(L_best==min(L_best));Shortest_Route=R_best(Pos(1),:)Shortest_Length=L_best(Pos(1))subplot(1,2,1)DrawRoute(C,Shortest_Route)subplot(1,2,2)plot(L_best)holdonplot(L_ave)functionDrawRoute(C,R)%%=====================================================%%DrawRoute.m%%畫路線圖的子函數(shù)%% %%CCoordinate節(jié)點(diǎn)坐標(biāo)，由一個(gè)Nx2的矩陣存儲(chǔ)%%RRoute路線%%=====================================================N=length(R);scatter(C(:,1),C(:,2));holdonplot([C(R(1),1),C(R(N),1)],[C(R(1),2),C(R(N),2)])holdonforii=2:Nplot([C(R(ii-1),1),C(R(ii),1)],[C(R(ii-1),2),C(R(ii)