模糊神经网络做数据预测的方法python
时间: 2023-12-11 18:05:34 浏览: 39
要使用模糊神经网络进行数据预测,可以使用Python中的Scikituzzy库。以下是一个简单的示例:
首先,安装Scikit-Fuzzy库:
```pythonpip install scikit-fuzzy
```
然后,导入所需的库:
```python
import numpy as np
import skfuzzy as fuzz
from skfuzzy import control as ctrl
```
接下来,定义输入和输出变量:
```python
# 定义输入变量
x = np.arange(0, 101, 1)
input_var = ctrl.Antecedent(x, 'input_var')
# 定义输出变量
y = np.arange(0, 101, 1)
output_var = ctrl.Consequent(y, 'output_var')
```
然后,定义模糊集合和隶属函数:
```python
# 定义模糊集合和隶属函数
input_var['low'] = fuzz.trimf(x, [0, 0, 50])
input_var['medium'] = fuzz.trimf(x, [0, 50, 100])
input_var['high'] = fuzz.trimf(x, [50, 100, 100])
output_var['low'] = fuzz.trimf(y, [0, 0, 50])
output_var['medium'] = fuzz.trimf(y, [0, 50, 100])
output_var['high'] = fuzz.trimf(y, [50, 100, 100])
```
然后,定义规则:
```python
# 定义规则
rule1 = ctrl.Rule(input_var['low'], output_var['low'])
rule2 = ctrl.Rule(input_var['medium'], output_var['medium'])
rule3 = ctrl.Rule(input_var['high'], output_var['high'])
```
接下来,创建控制器并添加规则:
```python
# 创建控制器并添加规则
fuzzy_ctrl = ctrl.ControlSystem([rule1, rule2, rule3])
fuzzy_prediction = ctrl.ControlSystemSimulation(fuzzy_ctrl)
```
最后,输入数据并进行预测:
```python
# 输入数据并进行预测
fuzzy_prediction.input['input_var'] = 70
fuzzy_prediction.compute()
print(fuzzy_prediction.output['output_var'])
```
这里的输入数据为70,预测输出将在中等水平(50-100)范围内。