模糊层次分析法 Python 代码实现指南
1. 流程图
flowchart TD
Start((开始))
Input((输入数据))
Step1((步骤1:构建判断矩阵))
Step2((步骤2:计算权重))
Step3((步骤3:一致性检验))
Output((输出最终结果))
Start --> Input
Input --> Step1
Step1 --> Step2
Step2 --> Step3
Step3 --> Output
2. 类图
classDiagram
class FuzzyAHP {
- calculate_matrix()
- calculate_weight()
- consistency_check()
}
3. 详细步骤及代码实现
步骤一:构建判断矩阵
# 导入必要的库
import numpy as np
# 构建判断矩阵
def calculate_matrix(criteria):
n = len(criteria)
matrix = np.zeros((n, n))
for i in range(n):
for j in range(n):
if i == j:
continue
matrix[i][j] = float(input(f"请输入{criteria[i]}相对于{criteria[j]}的重要性比例:"))
matrix[j][i] = 1 / matrix[i][j]
return matrix
步骤二:计算权重
# 计算权重
def calculate_weight(matrix):
n = len(matrix)
weight = np.zeros(n)
for i in range(n):
weight[i] = np.mean(matrix[i])
weight = weight / sum(weight)
return weight
步骤三:一致性检验
# 一致性检验
def consistency_check(matrix, weight):
n = len(matrix)
eigenvalue = np.dot(matrix, weight)
consistency_index = (eigenvalue - n) / (n - 1)
random_index = {1: 0, 2: 0, 3: 0.58, 4: 0.90, 5: 1.12, 6: 1.24, 7: 1.32, 8: 1.41, 9: 1.45}
lambda_max = sum(eigenvalue)
consistency_ratio = consistency_index / random_index[n]
if consistency_ratio < 0.1:
return True
else:
return False
结尾
通过上述代码和步骤,你可以实现模糊层次分析法在 Python 中的应用。记得在实践中不断尝试,加深理解,提升自己的编程能力。祝你成功!