如何使用Python实现模糊推理?
时间: 2024-03-28 13:31:51 浏览: 24
以下是使用Python实现模糊推理的步骤:
1. 安装依赖项:Python、scikit-fuzzy、numpy和matplotlib。可以使用pip install命令安装这些依赖项。
2. 导入所需库:
```python
import numpy as np
import skfuzzy as fuzz
from skfuzzy import control as ctrl
import matplotlib.pyplot as plt
```
3. 创建输入和输出变量:
```python
# 创建输入变量
quality = ctrl.Antecedent(np.arange(0, 11, 1), 'quality')
service = ctrl.Antecedent(np.arange(0, 11, 1), 'service')
# 创建输出变量
tip = ctrl.Consequent(np.arange(0, 26, 1), 'tip')
```
4. 创建模糊集合:
```python
# 创建模糊集合
quality.automf(3)
service.automf(3)
tip['low'] = fuzz.trimf(tip.universe, [0, 0, 13])
tip['medium'] = fuzz.trimf(tip.universe, [0, 13, 25])
tip['high'] = fuzz.trimf(tip.universe, [13, 25, 25])
```
5. 创建规则:
```python
# 创建规则
rule1 = ctrl.Rule(quality['poor'] | service['poor'], tip['low'])
rule2 = ctrl.Rule(service['average'], tip['medium'])
rule3 = ctrl.Rule(service['good'] | quality['good'], tip['high'])
```
6. 创建控制系统:
```python
# 创建控制系统
tipping_ctrl = ctrl.ControlSystem([rule1, rule2, rule3])
tipping = ctrl.ControlSystemSimulation(tipping_ctrl)
```
7. 输入模糊变量的值:
```python
# 输入模糊变量的值
tipping.input['quality'] = 6.5
tipping.input['service'] = 9.8
```
8. 运行控制系统:
```python
# 运行控制系统
tipping.compute()
```
9. 输出结果:
```python
# 输出结果
print(tipping.output['tip'])
```
完整的代码示例:
```python
import numpy as np
import skfuzzy as fuzz
from skfuzzy import control as ctrl
import matplotlib.pyplot as plt
# 创建输入变量
quality = ctrl.Antecedent(np.arange(0, 11, 1), 'quality')
service = ctrl.Antecedent(np.arange(0, 11, 1), 'service')
# 创建输出变量
tip = ctrl.Consequent(np.arange(0, 26, 1), 'tip')
# 创建模糊集合
quality.automf(3)
service.automf(3)
tip['low'] = fuzz.trimf(tip.universe, [0, 0, 13])
tip['medium'] = fuzz.trimf(tip.universe, [0, 13, 25])
tip['high'] = fuzz.trimf(tip.universe, [13, 25, 25])
# 创建规则
rule1 = ctrl.Rule(quality['poor'] | service['poor'], tip['low'])
rule2 = ctrl.Rule(service['average'], tip['medium'])
rule3 = ctrl.Rule(service['good'] | quality['good'], tip['high'])
# 创建控制系统
tipping_ctrl = ctrl.ControlSystem([rule1, rule2, rule3])
tipping = ctrl.ControlSystemSimulation(tipping_ctrl)
# 输入模糊变量的值
tipping.input['quality'] = 6.5
tipping.input['service'] = 9.8
# 运行控制系统
tipping.compute()
# 输出结果
print(tipping.output['tip'])
# 绘制输出变量的模糊集合
tip.view(sim=tipping)
plt.show()
```