文章基本信息

标题：エントロピー項付き正則化ファジィ推論モデルの提案
本地全文：下载
作者：Shinya FUKUMOTO ; Hiromi MIYAJIMA ; Yoji NAGASAWA 等
期刊名称：知能と情報
印刷版ISSN：1347-7986
电子版ISSN：1881-7203
出版年度：2004
卷号：16
期号：4
页码：372-380
DOI：10.3156/jsoft.16.372
出版社：Japan Society for Fuzzy Theory and Intelligent Informatics
摘要：This paper proposes a new fuzzy reasoning system with an entropy term as a regularization term in the objective function. Many studies have been done with fuzzy inference systems so far. Further, many improved models have been also proposed such as models using GA and self-organizing neural networks. The proposed fuzzy reasoning system has the objective function composed of the squared error and entropy terms: The former is the conventional objective one for the fuzzy reasoning system and the latter is a term which controls a shift of membership function. By adding the latter, learning of the system proceeds as degree of fitness of each rule approaches to 0.5. In order to demonstrate the validity of the proposed method, some numerical simulations are performed.
关键词：Entropy Term ; Fuzzy Reasoning Model ; Learning Method ; Squared Error