如何训练神经网络

Question

我最近遇到了这个神经网络并想运行它，但事实证明，它无法正确求解方程 a+b*c/d，显然它需要以某种方式进行训练，但我不太清楚了解如何去做。我最近才开始研究神经网络，如果您能提供帮助，我将不胜感激。

import numpy as np

# Define the neural network architecture
class NeuralNetwork:
    def __init__(self):
        self.weights = np.array([0.5, 0.5, 0.5])  # Weights for the input values

    def forward(self, inputs):
        return np.dot(inputs, self.weights)

# Define the equation to evaluate
equation = "2+3*10/9"

# Preprocess the equation
equation = equation.replace(" ", "")  # Remove any spaces

# Split the equation into operands and operators
operands = []
operators = []

current_operand = ""
for char in equation:
    if char.isdigit() or char == ".":
        current_operand += char
    else:
        operands.append(float(current_operand))
        current_operand = ""
        operators.append(char)

# Add the last operand
operands.append(float(current_operand))

# Create input array
inputs = np.array(operands[:-1])  # Exclude the last operand (result)

# Evaluate the equation using the neural network
neural_network = NeuralNetwork()
output = neural_network.forward(inputs)

# Apply the operators to the output sequentially
for operator, operand in zip(operators, operands[1:]):
    if operator == "+":
        output += operand
    elif operator == "-":
        output -= operand
    elif operator == "*":
        output *= operand
    elif operator == "/":
        output /= operand

# Print the result
print(f"Equation: {equation}")
print(f"Output: {output}")

我尝试寻找解决方案，但一无所获。

Answer 1

代码不包含任何训练过程。神经网络通过根据示例和损失函数调整权重来学习，而这里完全缺少这一点。