Every interval-valued metric can be naturally interpreted in fuzzy terms

Ildar Z. Batyrshin, Olga Kosheleva

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

Abstract

In situations when we do not have a good idea of what decision is the best, a natural idea is to look at similar situations in the past and see what worked in the past and what did not. From this viewpoint, it is important to design and study different measures of similarity. An efficient similarity measure must reflect our intuitive understanding of what is similar and what is not. Thus, when a general mathematical notion of a similarity measure is proposed, a reasonable question is how natural are measures satisfying this definition' One of the known measures of similarity are related to metrics (distance functions). It is known that every metric can be naturally interpreted in fuzzy terms. In this paper, we extend this interpretation to a more realistic case of interval-valued metrics and similarity measures.

Original languageEnglish
Title of host publication2015 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467372473
DOIs
StatePublished - 29 Sep 2015
EventAnnual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015 - Redmond, United States
Duration: 17 Aug 201519 Aug 2015

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
Volume2015-September

Conference

ConferenceAnnual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2015
Country/TerritoryUnited States
CityRedmond
Period17/08/1519/08/15

Keywords

  • Cities and towns
  • Electronic mail
  • Extraterrestrial measurements
  • Fuzzy logic
  • Fuzzy sets
  • Rivers

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