Fuzzy DEMATEL python source code
时间: 2023-07-31 16:11:35 浏览: 65
Here's an example of Fuzzy DEMATEL implementation in Python using the `numpy` and `skfuzzy` libraries:
```
import numpy as np
import skfuzzy as fuzz
def fuzzy_dematel(X, w):
# Normalize the input matrix X
X_norm = X / np.sum(X, axis=0)
# Calculate the fuzzy relation matrix
R = np.zeros((len(w), len(w)))
for i in range(len(w)):
for j in range(len(w)):
if i == j:
R[i][j] = 0
else:
R[i][j] = fuzz.interp_membership(X_norm[i], X_norm[j], w[j])
# Calculate the row-sum and column-sum vectors of the fuzzy relation matrix
row_sum = np.sum(R, axis=1)
col_sum = np.sum(R, axis=0)
# Calculate the normalized row-sum and column-sum vectors
norm_row_sum = row_sum / np.sum(row_sum)
norm_col_sum = col_sum / np.sum(col_sum)
# Calculate the impact matrix
I = np.zeros((len(w), len(w)))
for i in range(len(w)):
for j in range(len(w)):
if i == j:
I[i][j] = 0
else:
I[i][j] = norm_row_sum[i] * R[i][j] * norm_col_sum[j]
# Calculate the weights of the components
w_dematel = np.sum(I, axis=1) - np.sum(I, axis=0)
return w_dematel
```
The input matrix `X` should be a numpy array of size `(n_components, n_samples)`, where `n_components` is the number of components and `n_samples` is the number of samples. The weight vector `w` should be a numpy array of size `(n_components,)`.
To use this function, simply pass in your input matrix and weight vector, and it will return the weights of the components calculated using Fuzzy DEMATEL.