多属性决策分析案例结果

1、多属性决策分析案例( 分析过程文件见文件夹“分析过程”)第一步：利用 MATLAB 求综合属性值 M-FILE 源文件见“ multiattribute.m” 代码：%first import the data for A!%首先输入数组A (即文件“多属性决策”)！源数据顺序经过了调整，把逆指标放在 前23列，正指标放在后八列R=zeros(60,31);R1=zeros(60,31);E=zeros(1,31);W=zeros(1,31);Z=zeros(60,1);B=o nes(1,31);%把B变成全为1的数组k=1:23;B(1,k)=1./max(A(:,k)-min(A(:,k

2、); % 确定MAX(a(i,j)-MIN(a(i,j)数组 for j=1:23R(:,j)=(max(A(:,j)-A(:,j).*B(1,j);% 先把前23个逆指标规范化endB=ones(1,31);%再次把B变成全为1的数组 k=24:31;B(1,k)=1./max(A(:,k)-min(A(:,k);for j=24:31R(:,j)=(A(:,j)-min(A(:,j).*B(1,j)% 再把后八个正指标规范化for j=1:31R1(:,j)=R(:,j)./(sum(R(:,j);% 将矩阵 R列归一化ende=0;for j=1:1:31for i=1:1:60if R

3、1(i,j)=0s=0;else s=R1(i,j)*log(R1(i,j);ende=s+e;endE(j)=(-1/log(60)*e;% 得出信息熵endsK=sum(1-E(1,:);for j=1:31W(j)=(1-E(j)./sK;% 得出权重endfor i=1:60;z=0;for j=1:31z=z+R(i,j)*W(j);endZ(i)=z;%得出综合属性值Zendend“综合属性Z的数值综合属性值Z的具体数值见文件EXCLE第二步：用SPSS进行聚类分析分析结果聚类成员案例号VAR00002聚类距离11.001.01322.005.00233.004.01444.004

4、.00155.004.03166.004.01877.005.02488.005.01799.005.0221010.004.0121111.002.0181212.003.0061313.005.0161414.004.0001515.004.0141616.0057.511E-61717.002.0011818.002.0101919.002.0222020.001.0192121.004.0372222.003.0022323.001.0062424.004.0362525.002.0022626.004.0162727.004.0192828.003.0012929.004.01030

5、30.002.0303131.002.0143232.005.0023333.003.0093434.004.0243535.004.0233636.002.0173737.005.0103838.004.0023939.002.0164040.005.0074141.002.0024242.004.0054343.002.0074444.004.0034545.002.0324646.004.0214747.004.0244848.002.0234949.002.0065050.002.0125151.002.0175252.002.0175353.005.0245454.005.0075555.001.0125656.005.0205757.005.0075858.005.0135959.004.0216060.002.018最终聚类中心聚类1