Superiority of Proportional Fuzzy Sets to Decimal-Valued Fuzzy Set Extensions

Cengiz Kahraman*, Selcuk Cebi, Basar Oztaysi, Sezi Cevik Onar

*Corresponding author for this work

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

Abstract

Determination of membership, non-membership, and hesitancy degrees in the ordinary fuzzy sets and their extensions have not been sufficiently discussed in the literature. This study focusses on the ways of determining these degrees and tries to conclude which way is better than the others. We apply the same questionnaire to the participants of our experiment in four different days and want them to determine the membership degrees of the elements in the sets based on two different techniques. The aim of the experiment is to determine which way yields more stable degrees from the participants in different days.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference
EditorsCengiz Kahraman, Basar Oztaysi, Selcuk Cebi, Sezi Cevik Onar, Cagri Tolga, Irem Ucal Sari, Irem Otay
PublisherSpringer Science and Business Media Deutschland GmbH
Pages327-340
Number of pages14
ISBN (Print)9783031979842
DOIs
Publication statusPublished - 2025
Event7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 - Istanbul, Turkey
Duration: 29 Jul 202531 Jul 2025

Publication series

NameLecture Notes in Networks and Systems
Volume1528 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025
Country/TerritoryTurkey
CityIstanbul
Period29/07/2531/07/25

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

  • Decimal valued fuzzy sets
  • Proportional fuzzy sets
  • Proportional intuitionistic fuzzy sets
  • Proportional picture fuzzy sets

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