The whole algorithm is divided into three parts, the first part is to determine the overall structure of the neural networks, genetic algorithms and optimization of parameters, then that is a good use of the parameters have been optimized using neural networks to predict. We determine the length of the algorithm needs to be optimized according to the number of individual weights and thresholds. Individual fitness function is calculated by their fitness, according to the size of fitness, we use roulette algorithm to determine their genetic, crossover and mutation process as well as to optimize future BP neural network can better convergence.

拟合函数\BP.m
........\Code.m
........\Cross.m
........\data.mat
........\Decode.m
........\fun.m
........\Genetic.m
........\Mutation.m
........\Select.m
........\test.m
拟合函数

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