模糊综合评价法的python代码
时间: 2024-07-17 22:00:32 浏览: 147
模糊综合评价法(Fuzzy Comprehensive Evaluation, FCE)是一种在处理不确定性信息和模糊概念的多准则决策分析中常用的数学方法。在Python中,我们可以使用`skfuzzy`库来实现模糊集理论和模糊综合评价。以下是一个简单的步骤和代码示例:
首先,确保安装了`skfuzzy`库,如果没有,可以通过pip安装:
```bash
pip install skfuzzy
```
接下来,这是一个基本的模糊综合评价法的Python代码示例:
```python
# 导入必要的模块
from skfuzzy import control as ctrl
import numpy as np
# 定义模糊集(例如,对性能评价的模糊集)
def linguistic_varibles():
perf = ctrl.Antecedent(np.arange(0, 11), 'Performance')
perf['Poor'] = ctrl.trimf(perf.universe, [0, 0, 2])
perf['Average'] = ctrl.trimf(perf.universe, [2, 6, 8])
perf['Good'] = ctrl.trimf(perf.universe, [8, 10, 10])
reliability = ctrl.Antecedent(np.arange(0, 11), 'Reliability')
reliability['Low'] = ctrl.trimf(reliability.universe, [0, 0, 3])
reliability['Medium'] = ctrl.trimf(reliability.universe, [3, 7, 9])
reliability['High'] = ctrl.trimf(reliability.universe, [9, 10, 10])
return perf, reliability
# 定义评判矩阵和隶属函数
def fuzzy_matrix(perf, reliability):
# ...实际计算评判矩阵和隶属函数,这里省略
# 初始评价
def initial_evaluation(perf, reliability):
# ...根据实际情况计算初始评价,这里省略
return initial_score
# 合成评价
def comprehensive_evaluation(perf, reliability, fuzzy_matrix, initial_score):
def rule(performance, reliability):
return performance.defuzzify('Performance') * reliability.defuzzify('Reliability')
system = ctrl.ControlSystem([ctrl.Rule((perf['Poor'], reliability['Low']), rule)])
system_ctrl = ctrl.ControlSystemSimulation(system)
system_ctrl.input['Performance'] = initial_score['Performance']
system_ctrl.input['Reliability'] = initial_score['Reliability']
system_ctrl.compute()
final_score = system_ctrl.output['rule']
return final_score
# 使用函数
perf, reliability = linguistic_varibles()
fuzzy_matrix(perf, reliability)
initial_score = initial_evaluation(perf, reliability)
final_score = comprehensive_evaluation(perf, reliability, fuzzy_matrix, initial_score)
print("最终评价分数: ", final_score)