摘要
搜集和利用遗传算法运行过程中的知识,对于改善算法的性能有重要意义。文中采用BP前馈神经网络,动态学习遗传算法运动过程中的有关知识,并利用这些知识指导算法运行。实验结果表明本文方法能够改善算法的在线性能和寓线性能,提高遗传算法的寻优能力。
Gathering and using knowledge during the running of Genetic Algorithm has great significance in improving its performance. For this purpose, a new method named BPGA(BP network-based Genetic Algorithm) is developed by using BP neural network. The obtained knowledge is used to direct the running of GA. Experimental results show that BPGA algorithm improves the search ability, the on line performance and the off line performance of GA greatly.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
1999年第2期223-228,共6页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金
关键词
遗传算法
适应度函数
BP网络
Genetic Algorithm, Fitness Function, BP Network