Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/4242
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dc.contributor.authorMafarja, Majdi
dc.contributor.authorAbdullah, Salwani
dc.date.accessioned2017-02-14T07:39:59Z
dc.date.available2017-02-14T07:39:59Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/20.500.11889/4242
dc.description.abstractAttribute reduction can be defined as the process of determining a minimal subset of attributes from an original set of attributes. This paper proposes a new attribute reduction method that is based on a record-to-record travel algorithm for solving rough set attribute reduction problems. This algorithm has a solitary parameter called the DEVIATION, which plays a pivotal role in controlling the acceptance of the worse solutions, after it becomes pre-tuned. In this paper, we focus on a fuzzy-based record-to-record travel algorithm for attribute reduction (FuzzyRRTAR). This algorithm employs an intelligent fuzzy logic controller mechanism to control the value of DEVIATION, which is dynamically changed throughout the search process. The proposed method was tested on standard benchmark data sets. The results show that FuzzyRRTAR is efficient in solving attribute reduction problems when compared with other meta-heuristic approachesen_US
dc.language.isoen_USen_US
dc.subjectSystem theoryen_US
dc.subjectRough setsen_US
dc.subjectArtificial intelligenceen_US
dc.subjectFuzzy logicen_US
dc.subject.lcshAlgorithms
dc.titleA fuzzy record-to-record travel algorithm for solving rough set attribute reductionen_US
dc.typeArticleen_US
newfileds.departmentEngineering and Technologyen_US
newfileds.item-access-typeopen_accessen_US
newfileds.thesis-prognoneen_US
newfileds.general-subjectnoneen_US
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