A Study on Optimization of Automotive Suspension Base on PSO-BP Network Algorithm

摘要：

　　A BP neural network algorithm which bases on the particle swarm optimization (PSO) is advanced in this paper,Thus formed the PSO-BP network algorithm.It makes use of PSO to reach the global optimization of BP neural networks weight value and threshold value,and the optimized BP network is used to optimize the automotive suspension.Simulation results shows that this algorithm can improve the weak points of the BP leaming algorithm such as the slow convergence rate and the poor global covergence.It can also reduce the number of training and the error obviously.

关键词： PSO-BP algorithm BP neural network particle swarm optimization automotive suspension parameter optimization

作者: Jiang Chang-song Li You-de Wang Zhong-dong

作者单位: College of Plant Science, Jilin University The xi an Road No.5333, Changchun City, P.R.China, 13006 College of Automotive Engineering, Jilin University The People Street No.5988, Changchun City, P.R.C Teaching Center of Basic Courses, Jilin University The xi an Road No.5333, Changchun City, P.R.Chin

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 3760-3764

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）