A ranking approach with inclusion measure in multiple-attribute interval-valued decision making

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

4 Scopus citations

Abstract

This paper first presents a brief survey of the existing works on comparing and ranking any two interval numbers and then, on the basis of this, gives the inclusion measure approach to compare any two interval numbers. The monotonic inclusion measure is defined over the strict partial order set proposed by Moore and illustrate that the possibility degrees in the literature are monotonie inclusion measures defined in this paper; Then a series of monotonic inclusion measures are constructed based on t-norms. Finally, we give illustrations by using the monotonic inclusion measures and gain good results.

Original languageEnglish
Title of host publicationRough Sets, Fuzzy Sets, Data Mining and Granular Computing - 11th International Conference, RSFDGrC 2007, Proceedings
PublisherSpringer Verlag
Pages411-418
Number of pages8
ISBN (Print)9783540725299
DOIs
StatePublished - 2007
Event11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007 - Toronto, Canada
Duration: 14 May 200717 May 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4482 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computer, RSFDGrC 2007
Country/TerritoryCanada
CityToronto
Period14/05/0717/05/07

Keywords

  • Inclusion measure
  • Multipleattribute decision making
  • Ranking of interval number

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