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Fuzzy rough sets based on hybrid monotonic inclusion measures and similarity measures

  • Xi'an Shiyou University
  • Xidian University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Rough set theory and fuzzy set theory hold the topic of dealing with imperfect knowledge. Recent literature have shown both theories can be combined into a more expressive framework for modeling and processing incomplete information systems. According to the hierarchical characteristic of fuzzy sets, this paper presents the definitions of λ-weak fuzzy approximation space and ISλ-fuzzy rough set based on a hybrid monotonic inclusion measure and a similarity measure. The properties of the ISλ- fuzzy rough set are investigated. The approximate operators of a fuzzy decision concept and the relative decision rules will be derived from the fuzzy rough approximate operators.

Original languageEnglish
Title of host publication2010 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2010
DOIs
StatePublished - 2010
Event2010 Annual North American Fuzzy Information Processing Society Conference, NAFIPS'2010 - Toronto, ON, Canada
Duration: 12 Jul 201014 Jul 2010

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

Conference2010 Annual North American Fuzzy Information Processing Society Conference, NAFIPS'2010
Country/TerritoryCanada
CityToronto, ON
Period12/07/1014/07/10

Keywords

  • Decision rule
  • Fuzzy rough sets
  • Hybrid monotonic inclusion measure

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