提出了以基因算法为基础的人工神经元网络结构设计基础。首先从连接权的演化入手,研究了基因算法的实现过程。在结构设计中,提出了稀疏化的编码方法。仿真结果表明这种优化方法对于神经网络的选取是有效的。
Abstract
A system for the architecture design of artificial neural network based on the genetic algorithm(GA) is proposed. With the evolution of connection weights first, the author researches into the materialization of GA, and a combined genetic/back-propagation learning algorithm is hence proposed. In the development of neural network's architectures, a sparse coding is put forward. Simulation results show that this optimization method is efficient for selecting ANN's structures.
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 焦李成. 神经网络系统理论. 西安:西安电子科技大学出版社,1992
[2] 高彦臣,李大字. 利用基因算法实现参数优化的研究.北京化工大学学报,1995 ,22 (1) :53~58
[3] 田盛丰,陈峰,任建宏. 人工智能原理与应用. 北京:北京理工大学出版社,1993
[4] 李大字. 基因算法辅助人工神经元网络的结构设计.[学位论文] . 北京:北京化工大学,1995
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}