关键词: 模拟退火, 混合递阶遗传算法, 径向基神经网络, 故障诊断

Abstract: An optimization method of RBF neural network based on simulated annealing and hybrid hierarchy genetic algorithm is put forward. In this method, the network topology, centers and radius of RBF neural network are optimized by hybrid hierarchy genetic algorithm, the probabilities of cross and mutation in genetic algorithm are controlled by simulated annealing algorithm, and the output weights of network are calculated by least square method. To validate the feasibility and effectiveness, this method and other four methods are implemented in typical case, the result shows that the accuracy of the proposed method is obviously higher than other methods. The feasibility and superiority of the method are validated.

Key words: Simulated Annealing（SA）, Hybrid Hierarchy Genetic Algorithm（HHGA）, Radial Basic Function Neural Network（RBFNN）, fault diagnosis