matlab.txt

模糊控制

clear;clc;
a=[
48.37611111 26.33277778 819.1455556 334.5933333 1032.364444 262.3716667 2374.722222
15.84 6.430384615 981.3157692 756.1965385 991.7353846 82.82846154 2535.692308
70.7225 29.8525 895.5325 294.5875 1059.1875 462.9525 2724.5
]; %a为评价集标准值
d=[
43.49 28.05 737.98 391.12 1025.66 7.41 2134
2.61 1.82 920.75 636.41 1005.45 74.09 2330
28.66 8.51 774.99 322.78 1013.96 93.84 2001
3.01 1.95 897.53 614.44 889.87 123.27 2200
25.85 5.72 759.59 302.03 1001.96 76.15 1972
2 1.95 1161.68 1003.73 1077.06 110.1 3004
3.81 1.09 820.51 396.61 1004.74 37.04 2019
5.21 2.92 814.08 419.8 1005.8 31.49 2018
4.41 2.8 824.65 449.06 998.36 38.28 2047
3.01 1.58 1220.54 956.14 1244.75 3.91 3071
6.01 2.43 1791.61 2338.17 1278.08 30.87 4362
1.2 2.67 1160.54 821.29 1100.82 85.41 2942
6.61 7.3 865.57 389.31 1065.27 46.51 2244
9.82 3.77 1240.77 939.71 1165.24 177.19 3248
17.64 6.44 884.2 473.49 930.29 218.95 2417
26.65 7.9 839.5 474.71 941.99 184.18 2363
25.25 4.74 808.33 486.31 881.01 191.6 2217
25.45 6.93 852.01 478.37 966.45 182.54 2339
35.27 18.48 785.11 331.32 979.57 4.04 2245
2.81 2.31 1601.02 2533.55 486.73 2.47 3801
4.21 4.86 1815.52 2584.68 963.61 0 4399
15.23 5.35 813.85 787.16 688.79 205.18 2093
67.01 36.65 864.23 357.76 1035.8 426.31 2609
84.65 34.24 892.72 381.19 1060 466.64 2731
15.43 21.52 898.68 88.47 1061.46 414.48 2483
115.8 27 926.5 350.93 1079.49 544.38 3075

]; %b为待判样品值

[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
                    for k = 1 : m
                        if a(i, j) == c(k, j) 

                            if 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
                            end

                            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
                            if 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
                    end
               end
    end
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %权重乘以单因素隶属度得到最终结果
     R=LSDResult;
     E=EResult;
    FuzzyEvalution=E*R;
    TheResultMoHu=[TheResultMoHu;FuzzyEvalution];
end
TheResultMoHu