A New Kind of Optimization Method for Gear Design

摘要：

　　In order to raise the design efficiency and get the most excellent design effect, this paper combined Particle Swarm Optimization (PSO) algorithm and put forward a new kind of neural network, based on PSO algorithm and NARMA model.It gives the basic theory, steps and algorithm; The test results show that rapid global convergence and reached the lesser mean square error MSE) when compared with Genetic Algorithm, Simulated Annealing Algorithm, the BP algorithm with momentum term.

关键词： Neural network (NN) Particle Swarm Optimization (PSO) Monopole-Gear

作者: Yuguo Wu

作者单位: School of Mechanical Engineering,Anhui University of Technology,Maanshan,Anhui,China,243002

会议类型: 国际会议

会议名称: the 3nd International Conference on Digital Manufacturing & Automation (第三届数字制造与自动化国际会议(ICDMA 2012))

会议地点: 桂林

会议语种:英文

页码: 7-10

在线出版日期: 2012-08-01（万方平台首次上网日期，不代表论文的发表时间）