NDLI: A Rule Reasoning Method and Its Application

Content Provider	IEEE Xplore Digital Library
Author	Liu Fuyan Lv Shaoyi Chen Chouyong
Copyright Year	2005
Description	Author affiliation: Hangzhou Dianzi Univ. (Liu Fuyan; Lv Shaoyi; Chen Chouyong)
Abstract	In this paper we present a rule reasoning method, which is based on rough sets theory, for inducing rules from examples. The key idea of the method is that it combines a criterion of the dependency degree of attributes with decision makers' priori knowledge to select attributes of objects. Especially, it uses a compound weights algorithm to perform a proper reduction owing to several reductions that each rule can have and select the most effective attribute subset. As a result, a practical and effective reduced knowledge rule set can be acquired. In order to evaluate the effectiveness of the method, we apply the obtained knowledge rule set to optimization control of a prototype simulation system. Experimental results show that the rule reasoning method is more efficient
Sponsorship	Univ. of Aizu, Japan Nat. Natural Sci. Found. China Fudan GrandHorizon Inf. Technol., Inc. China Hewlett-Packard Co., Ltd
Starting Page	39
Ending Page	43
File Size	196091
Page Count	5
File Format	PDF
ISBN	076952432X
DOI	10.1109/CIT.2005.46
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Induction generators Rough sets Optimization methods Knowledge representation Machine learning Set theory Feature extraction Data mining Virtual prototyping Context modeling
Content Type	Text
Resource Type	Article

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