中文说明：
该案例的功能是使用遗传算法优化BP神经网络，分为BP神经网络结构确定、遗传算法优化和BP神经网络预测三个部分。遗传算法优化使用遗传算法优化BP神经网络的权值和阈值，种群中的每个个体都包含了一个网络所有权值和阈值，种群中的每个个体都包含了一个网络所有权值和阈值，个体通过适应度函数计算个体适应度值，遗传算法通过选择，交叉和变异操作找到最优适应度值对应个体。
English Description：
The function of this case is to use genetic algorithm to optimize BP neural network, which is divided into three parts: structure determination of BP neural network, optimization of genetic algorithm and prediction of BP neural network. Genetic algorithm optimization uses genetic algorithm to optimize the weights and thresholds of BP neural network. Each individual in the population contains a network ownership value and threshold value, and each individual in the population contains a network ownership value and threshold value. The individual calculates the individual fitness value through the fitness function, and the genetic algorithm finds the optimal fitness value through selection, crossover and mutation operations Corresponding individuals.