A fuzzy record-to-record travel algorithm for solving rough set attribute reduction

Majdi Mafarja, Salwani Abdullah

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Attribute 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 approaches.

Original languageEnglish
Pages (from-to)503-512
Number of pages10
JournalInternational Journal of Systems Science
Volume46
Issue number3
DOIs
Publication statusPublished - 25 Feb 2015

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Attribute Reduction
Rough Set
Attribute
Fuzzy Logic Controller
Reduction Method
Metaheuristics
Fuzzy logic
Benchmark
Controllers
Subset

Keywords

  • attribute reduction
  • fuzzy logic
  • record-to-record travel algorithm
  • rough set theory

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications

Cite this

A fuzzy record-to-record travel algorithm for solving rough set attribute reduction. / Mafarja, Majdi; Abdullah, Salwani.

In: International Journal of Systems Science, Vol. 46, No. 3, 25.02.2015, p. 503-512.

Research output: Contribution to journalArticle

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