%求模糊等价矩阵
function B=calBibao(R)
a=size(R);
B=zeros(a);
flag=0;
while flag==0for i= 1: afor j= 1: a for k=1:a B( i , j ) = max(min( R( i , k) , R( j, k) ) , B( i , j ) ) ;%R与R内积，先取小再取大endendendif B==R  %矩阵B为等价矩阵 flag=1;      else R=B;%循环计算R传递闭包 end
end

%利用截关系对R^k进行等价分类的结果
function simil=calIntercept(A,lambda)
row = size(A,1);%x矩阵行数
col = size(A,2);%x矩阵列数
I = zeros(row,col);
simil = zeros(1,26);
%不断地降低lambda的值，输出similiar向量，对比发现与第七行最相近的行
for i=1:rowfor j=1:colif A(i,j)>=lambdaI(i,j)=1;elseI(i,j)=0;endend
end
k=1;
for j=1:26if I(7,:)==I(j,:)simil(1,k)=j;k=k+1;      end
end

%计算模糊相似矩阵
function fs=calFuzzySim(x)
tic;
row = size(x,1);%x矩阵行数
col = size(x,2);%x矩阵列数
fs = zeros(row,row);
for j=1:rowfor i=1:rownumerator=0;denominator=0;for k=1:colnumerator = numerator+min(x(i,k),x(j,k));denominator = denominator+max(x(i,k),x(j,k));endfs(i,j)=numerator/denominator;end
end
dettime=toc;%fprintf('calFuzzySim took %.1f seconds\n',dettime);

%逐渐降低lambda值，通过截关系进行等价分类
function simil2=calRelat(A)
measure= 0.995:-0.01:0.295;
len=length(measure);
simil2=zeros(len,26);
for i= 1:lensimil2(i,:)=calIntercept(A,measure(1,i));
end

a=[36,41,63,65,60;
60,48,66,80,63;
51,54,81,81,94;
64,56,86,85,83;
51,50,35,31,37;
39,57,65,68,70;
60,59,97,100,96;
62,58,94,97,91;
66,51,83,85,86;
50,38,17,52,18;
43,18,43,40,16;
68,67,65,89,79;
55,60,23,66,66;
39,33,15,15,38;
45,44,29,70,45;
61,48,63,72,65;
49,73,65,82,64;
59,59,65,67,62;
54,62,47,80,95;
41,33,9,10,32;
56,59,77,75,92;
30,43,77,67,75;
46,50,24,36,25;
20,37,17,54,40;
57,53,41,78,60;
55,28,35,60,36]