Application of improved genetic algorithm in optimizing BP neural networks weights
Yao Mingha · Computer Engineering and Applications Journal · 2013
The characteristics of genetic algorithm and BP neural networks are compared. As evolutionary algorithm neural net- work and genetic algorithm have same goal but they have different methods. The necessity of the combination genetic algorithm and neural networks is expounded. This paper puts forward a kind of improved genetic algorithm to optimize BP neural network weights, using the global random searching ability of genetic algorithm to make up the question that neural network is easy to fall into local optimal solution. At the same time, the crossover method of genetic algorithm is changed. The same generation does not cross. The parent and son are crossed. Genetic algorithm premature loss of evolutionary ability is averted.