首页熵权法和critic权重法matlab代码

熵权法和critic权重法matlab代码

时间: 2025-03-02 10:19:19 浏览: 95

### MATLAB 实现熵权法熵权法是一种常用的多属性决策方法，用于确定各评价指标的权重。以下是该方法的一个简单实现： ```matlab function weights = entropy_weight_method(data) % data: m x n matrix where rows represent alternatives and columns attributes [m, n] = size(data); % Step 1: Normalize the decision matrix norm_data = data ./ sum(data, 1); % Step 2: Calculate the probability distribution p_ij = norm_data ./ repmat(sum(norm_data), m, 1); % Avoid log(0) issue epsilon = eps; p_ij(p_ij == 0) = epsilon; % Step 3: Compute entropy values for each attribute e_j = -sum(p_ij .* log(p_ij)) / log(m); % Step 4: Determine difference coefficient d_j d_j = 1 - e_j; % Step 5: Calculate final weights w_i weights = d_j ./ sum(d_j); end ``` 此函数接收一个矩阵作为输入参数 `data`，其中每一列表示不同属性的数据。 ### CRITIC 权重法的 MATLAB 实现 CRITIC 方法考虑了数据变异性和冲突性两个方面来计算权重。下面是一个基本实现方式： ```matlab function weights = critic_weight_method(data) % data: m x n matrix where rows represent alternatives and columns attributes [~, n] = size(data); % Standard deviation calculation std_devs = std(data, [], 1); % Correlation coefficients between all pairs of criteria corr_matrix = corrcoef(data'); conflict_measures = zeros(n, 1); for i = 1:n temp_corr_vector = abs(corr_matrix(i,:)); temp_corr_vector(i)=[]; % Remove self-correlation conflict_measures(i) = sum(temp_corr_vector); end % Critic factor computation critic_factors = std_devs .* (1 .- conflict_measures); % Normalization to get weights weights = critic_factors ./ sum(critic_factors); end ``` 这两个算法都遵循各自理论框架下的标准流程[^1]。

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