用Java写一段神经网络代码

╰+攻爆jí腚メ 2024-03-27 17:55 80阅读 0赞

好的，这是用 Java 写的一段简单的神经网络代码的例子。这个神经网络有两个输入层单元、一个隐藏层单元、一个输出层单元，并且使用 sigmoid 激活函数。

\`\`\` import java.util.Random;

public class NeuralNetwork \{ // 输入层单元数量 private final int inputSize; // 隐藏层单元数量 private final int hiddenSize; // 输出层单元数量 private final int outputSize;

// 输入层到隐藏层的权重矩阵 private final double\[\]\[\] weightsInputToHidden; // 隐藏层到输出层的权重矩阵 private final double\[\]\[\] weightsHiddenToOutput;

// 随机数生成器，用于初始化权重 private final Random random;

public NeuralNetwork(int inputSize, int hiddenSize, int outputSize) \{ this.inputSize = inputSize; this.hiddenSize = hiddenSize; this.outputSize = outputSize;

weightsInputToHidden = new double[inputSize][hiddenSize];
    weightsHiddenToOutput = new double[hiddenSize][outputSize];
    
    random = new Random();
    // 随机初始化权重
    for (int i = 0; i < inputSize; i++) {
          
      for (int j = 0; j < hiddenSize; j++) {
          
        weightsInputToHidden[i][j] = random.nextDouble();
      }
    }
    for (int i = 0; i < hiddenSize; i++) {
          
      for (int j = 0; j < outputSize; j++) {
          
        weightsHiddenToOutput[i][j] = random.nextDouble();
      }
    }

public double\[\] predict(double\[\] input) \{ if (input.length != inputSize) \{ throw new IllegalArgumentException("Invalid input size."); \}

// 输入层到隐藏层的输出
    double[] hiddenOutput = new double[hiddenSize];
    for (int i = 0; i < hiddenSize; i++) {
      double sum = 0.0;
      for (int j = 0; j < inputSize; j++) {
        sum += input[j] * weightsInputToHidden[j][i];
      }
      hiddenOutput[i] = sigmoid(sum);
    }
    
    // 隐藏层到