Design Optimization Based on Neural Networks And Ant Colony Optimization

摘要：

In order to raise the design efficiency and get the most excellent design effect, this paper combined Ant Colony Optimization (ACO) algorithm and neural networks, which based on ACO algorithm and the implementing framework of ACO. It gives the basic theory and steps; 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.

作者: Wu Yu GUO Song Chong ZHI

作者单位: AnHui University of Technology, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）