A new approach to fuzzy classifier systems and its application in self-generating neuro-fuzzy systems

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Computer Science and Information Engineering > journal & Dissertation > Item 987654321/31831

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/31831

Title:	A new approach to fuzzy classifier systems and its application in self-generating neuro-fuzzy systems
Authors:	Su,MC;Chou,CH;Lai,E;Lee,J
Contributors:	資訊工程研究所
Keywords:	LEARNING CONTROL NETWORK;REINFORCEMENT;PERFORMANCE
Date:	2006
Issue Date:	2010-07-06 18:12:29 (UTC+8)
Publisher:	中央大學
Abstract:	A classifier system is a machine learning system that learns syntactically simple string rules (called classifiers) through a genetic algorithm to guide its performance in an arbitrary environment. In a classifier system, the bucket brigade algorithm is u
Relation:	NEUROCOMPUTING
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	416	View/Open

社群 sharing