The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression

Sharifah Sakinah, Syed Ahmad and Pedrycz, Witold (2016) The Development Of Granular Rule-Based Systems: A Study In Structural Model Compression. Granular Computing. pp. 1-12. ISSN 2364-4966

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Abstract

In this study, we develop a comprehensive design process of granular fuzzy rule-based systems. These constructs arise as a result of a structural compression of fuzzy rule-based systems in which a subset of originally existing rules is retained. Because of the reduced subset of the originally existing rules, the remaining rules are made more abstract (general) by expressing their conditions in the form of granular fuzzy sets (such as interval-valued fuzzy sets, rough fuzzy sets, probabilistic fuzzy sets, etc.), hence the name of granular fuzzy rule-based systems emerging during the compression of the rule bases. The design of these systems dwells upon an important mechanism of allocation of information granularity using which the granular fuzzy rules are formed. The underlying optimization consists of two phases: structural (being of combinatorial character in which a subset of rules is selected) and parametric (when the conditions of the selected rules are made granular through an optimal allocation of information granularity). We implement the cooperative particle swarm optimization to solve optimization problem. A number of experimental studies are reported; those include fuzzy rule-based systems.

Item Type:	Article
Uncontrolled Keywords:	Rule-based systems; Structural compression; Optimal allocation of information granularity; Particle swarm optimization; Granular fuzzy sets
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	10 Oct 2016 00:45
Last Modified:	12 Sep 2021 23:38
URI:	http://eprints.utem.edu.my/id/eprint/17282
Statistic Details:	View Download Statistic

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