MATLAB中计算熵权topsisi的代码
时间: 2023-07-29 20:12:13 浏览: 80
计算熵权TOPSIS方法需要用到MATLAB中的矩阵运算和函数,以下是MATLAB代码示例:
```matlab
% 输入数据矩阵,每行代表一个评价对象,每列代表一个评价指标
data = [1 2 3 4; 2 3 4 5; 3 4 5 6; 4 5 6 7];
% 标准化处理
[m, n] = size(data);
data_normalized = zeros(m, n);
for i = 1:n
data_normalized(:, i) = data(:, i) ./ sum(data(:, i));
end
% 计算熵权
entropy = -sum(data_normalized .* log(data_normalized), 1);
weight = (1 - entropy) / sum(1 - entropy);
% 计算距离矩阵
data_normalized_weighted = data_normalized .* weight;
ideal_best = max(data_normalized_weighted, [], 1);
ideal_worst = min(data_normalized_weighted, [], 1);
distance_best = sqrt(sum((data_normalized_weighted - ideal_best) .^ 2, 2));
distance_worst = sqrt(sum((data_normalized_weighted - ideal_worst) .^ 2, 2));
% 计算TOPSIS综合评价指数
score = distance_worst ./ (distance_best + distance_worst);
```
其中,`data`为输入的数据矩阵,`data_normalized`为标准化后的矩阵,`entropy`为熵权向量,`weight`为熵权向量的归一化权重向量,`ideal_best`和`ideal_worst`分别为最优和最劣方案,`distance_best`和`distance_worst`分别为距离最优和最劣方案的欧氏距离,`score`为综合评价指数。