Optimization algorithm of PSO-BPNN based on extended T-S fuzzy model

Mechanical equipment with fuzzy and non-linear characteristics,a new structured intelligence method is proposed based on extended T-S(Takagi-Sugeno) fuzzy model of self-adaptive Particle Swarm Optimization(PSO) algorithm and BP Neural Network(BPNN) algorithm.The basic T-S fuzzy model is modified,and the parameter in PSO algorithm is adjusted by extended T-S fuzzy model.The BPNN with hidden layer neurons number of design variables,after extraction of the mean square error as the evaluation function,with the improved particle swarm optimization algorithm.The optimized structure of the network model is applied to optimize the wheelt,he test results show that the method to ensure the performance of wheel at the same timei,ts structure is clear that re-optimization is a feasible method of structural optimization.