文章基本信息

标题：Neural Network Learning based on Chaos
作者：Truong Quang Dang Khoa ; Masahiro Nakagawa
期刊名称：International Journal of Computer, Information, and Systems Science, and Engineering
印刷版ISSN：1307-2331
出版年度：2007
卷号：1
期号：2
出版社：World Academy of Science, Engineering and Technology
摘要：Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depthfirst search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.
关键词：Learning and Evolutionary Computing, Chaos optimization algorithm, Artificial Neural Networks, Nonlinear optimization, Intelligent Computational Technologies.