GENETIC ALGORITHM-BASED RESONANT CONVERTER DESIGN PARAMETER SELECTION METHOD

Disclosed is a genetic algorithm-based resonant converter design parameter selection method. According to the present invention, multi-target parameter solution vectors can be naturally obtained in an initial solution global solution set population space under a convergence condition by using a genetic algorithm; a BP neural network can adaptively obtain a population space φ* by means of the initial solution global solution set population space; by means of a proper hybridization operator and mutation operator, according to a roulette wheel selection operator, proper male parents and female parents are selected from these solution vectors having higher fitness, and genes of the male parents and the female parents are disassembled and recombined, so as to generate solution vectors in a sub-generation; then the fitness of these solution vectors in the sub-generation is calculated by means of a natural selection function; and generations of heredity is performed in the same way, and finally convergence is perfor