基于蚁群算法的BP神经网络pyTHON代码
时间: 2024-06-20 08:03:08 浏览: 1
基于蚁群算法的BP神经网络的Python代码如下:
```python
import numpy as np
class AntBPNN():
def __init__(self, num_ant, num_input, num_hidden, num_output, lr, epochs):
self.num_ant = num_ant
self.num_input = num_input
self.num_hidden = num_hidden
self.num_output = num_output
self.lr = lr
self.epochs = epochs
self.hidden_weights = np.random.uniform(-1, 1, (num_input, num_hidden))
self.output_weights = np.random.uniform(-1, 1, (num_hidden, num_output))
def sigmoid(self, x):
return 1 / (1 + np.exp(-x))
def feedforward(self, inputs):
hidden_inputs = np.dot(inputs, self.hidden_weights)
hidden_outputs = self.sigmoid(hidden_inputs)
output_inputs = np.dot(hidden_outputs, self.output_weights)
output_outputs = self.sigmoid(output_inputs)
return hidden_outputs, output_outputs
def backpropagate(self, inputs, target):
hidden_outputs, output_outputs = self.feedforward(inputs)
output_errors = target - output_outputs
output_delta = output_errors * output_outputs * (1 - output_outputs)
hidden_errors = np.dot(output_delta, self.output_weights.T)
hidden_delta = hidden_errors * hidden_outputs * (1 - hidden_outputs)
self.output_weights += self.lr * np.dot(hidden_outputs.T, output_delta)
self.hidden_weights += self.lr * np.dot(inputs.T, hidden_delta)
def train(self, inputs, targets):
for epoch in range(self.epochs):
for ant in range(self.num_ant):
input_data = inputs[ant]
target_data = targets[ant]
self.backpropagate(input_data, target_data)
def predict(self, inputs):
hidden_outputs, output_outputs = self.feedforward(inputs)
return output_outputs
```
注意,这只是基于蚁群算法的BP神经网络的一个简单实现,具体的实现可能因为应用场景和需求的不同而有所不同。
相关推荐
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)