Optimization of turbine disk based on particle swarm optimization and neural network

A new computational intelligence method was established by combining particle swarm optimization(PSO) and back propagating(BP) neural network.In addition to structural optimization,PSO is also used in BP neural network's construction and training,thus enabling self-adaptive optimization.In the structural optimization,the neural networks were used to map object function and constraints instead of finite element method(FEM),helping to accelerate greatly the computation speed.A disk model was optimized to decrease its volume by 17.5%.The results show that,this convenient and efficient method will provide a new approach to structural optimization.