function TheResultMoHu = fce(a, d)
% a 为评价集标准值
% d 为待判样品值
%
% Program modification from http://www.pudn.com/Download/item/id/2798831.html
% code update on 2018-03-19
% A.Star, Snowland Co. Ltd, chenxiaolong12315@163.com
% Example:
%     a=[0.9 0.9 0.9 0.9;
%        0.7 0.7 0.7 0.7;
%        0.5 0.5 0.5 0.5;
%        0.3 0.3 0.3 0.3;
%        0.1 0.1 0.1 0.1;
%     ];
%     d=[
%         0.92	0.9	0.86	0.88;
%     0.93	0.88	0.87	0.89;
%     0.67	0.68	0.78	0.79;
%     0.73	0.78	0.75	0.69;
%     0.58	0.52	0.57	0.43;
%     0.41	0.54	0.44	0.42;
%     0.31	0.27	0.22	0.4;
%     0.35	0.36	0.23	0.28;
%     0.16	0.18	0.19	0.18;
%     0.05	0.15	0.07	0.13;
%     ];
%     res = fce(a, d)

[m,n]=size(a);
[x,y]=size(d);
TheResultMoHu=[];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for s=1:x
    for p=1:n
        b(p)=d(s,p);
    end
    for i=1:n %计算每一个列的平均值
        ColAverage(i)=0;
        for j=1:m
            ColAverage(i)=ColAverage(i)+a(j,i);
        end
        ColAverage(i)=ColAverage(i)/m;
    end
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        ETotal = 0; %超标加权法计算权重
        for j = 1: n
             ETotal = ETotal + (b(j) / ColAverage(j));
        end
        for i = 1: n
            EResult(i) = (b(i) / ColAverage(i)) / ETotal; %EResult为计算结果
        end
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %使用隶属函数，做预处理对每一列进行排序
    SortedMatrix=a;
    for j=1:n
        for i=1:m
            for k=i:m
                if SortedMatrix(i,j)>SortedMatrix(k,j)
                    tmp=SortedMatrix(i,j);
                    SortedMatrix(i,j)=SortedMatrix(k,j);
                    SortedMatrix(k,j)=tmp;
                end
            end
        end
    end
    
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %计算单因素隶属度
    
    c=SortedMatrix;
    for j = 1 : n
        for i = 1 : m
            k = 1;
            if b(j) < c(k, j)
                LSDResult(j, i) = 1;
            end
            if b(j) >= c(k, j) & b(j) < c(k + 1, j)
                LSDResult(j, i) = ((c(k + 1, j) - b(j)) / (c(k + 1, j) - c(k, j)));
            end
            if b(j) >= c(k + 1, j)
                LSDResult(j, i) = 0;
            end
            
            for k = 2 : m-1
                if a(i, j) == c(k, j)                 
                    if k > 1 & k < m
                        
                        if b(j) < c(k - 1, j)
                            LSDResult(j, i) = 0;
                        end
                        if b(j) >= c(k - 1, j) & b(j) < c(k, j)
                            LSDResult(j, i) = ((b(j) - c(k - 1, j)) / (c(k, j) - c(k - 1, j)));
                        end
                        if b(j) >= c(k, j) & b(j) < c(k + 1, j)
                            LSDResult(j, i) = ((c(k + 1, j) - b(j)) / (c(k + 1, j) - c(k, j)));
                        end
                        if b(j) >= c(k + 1, j)
                            LSDResult(j, i) = 0;
                        end
                    end
                end
            end
            k = m;
            
            if b(j) < c(k - 1, j)
                LSDResult(j, i) = 0;
            end
            if b(j) >= c(k - 1, j) & b(j) < c(k, j)
                LSDResult(j, i) = ((b(j) - c(k - 1, j)) / (c(k, j) - c(k - 1, j)));
            end
            if b(j) >= c(k, j)
                LSDResult(j, i) = 1;
                
            end
        end
    end
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %权重乘以单因素隶属度得到最终结果
    R=LSDResult;
    E=EResult;
    E=[0.4236 0.227 0.1224 0.2771];
    FuzzyEvalution=E*R;
    TheResultMoHu=[TheResultMoHu;FuzzyEvalution];
end
end