摘要
随着生产规模的复杂化,多维化和非线形等复杂特性,对高效的优化技术的要求也越迫切,利用并行遗传算法和Hopfield网络的优点,提出了采用遗传算法的并行搜索和解空间搜索的优点进行网络参数的选取,利用Hopfield网络简单、快速、规范的优点来优化样本空间,以取得整体的优化效率。
With the complication,multiple dimension and nonlinearity of manufacture scale,much more optimization technology is needed. The author takes the advantage of parallel GA and Hopfield NN to put forward a optimization design method based on NN and GA to obtain unitary efficiency,which uses the GAs parallel searching and solution space searching to find the good parameters of the net. Then uses the Hopfields simple,rapid and criterion to optimize the sample space.
出处
《计算机应用》
CSCD
北大核心
2003年第10期98-99,共2页
journal of Computer Applications
基金
江苏省自然科学基金项目 (0 1JKB 0 0 0 3 )
