Genetic algorithm to optimize BP neural network is designed by means of genetic algorithms get better network initial weights and thresholds, the basic idea is to use individual represents the network' s initial weights and thresholds, the individual values ​ ​ initialized BP neural network prediction error as the individual' s fitness value, through selection, crossover and mutation to find the optimal individual, ie the optimal BP neural network initial weights. In addition to genetic algorithms, you can also use particle swarm optimization, ant colony algorithm to optimize BP neural network initial weights.

Genetic algorithm optimization\BP.m
..............................\Code.m
..............................\Cross.m
..............................\data.mat
..............................\Decode.m
..............................\fun.m
..............................\Genetic.m
..............................\Mutation.m
..............................\Select.m
..............................\test.m
..............................\运行说明.txt
Genetic algorithm optimization

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