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International Conference on Intelligent and Fuzzy Systems

INFUS 2019: Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making pp 770–778Cite as

Evaluation of Social Sustainable Development Factors Using Buckley’s Fuzzy AHP Based on Z-Numbers

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1029))

Abstract

Analytical Hierarchy Process (AHP) has been extended by several extensions of ordinary fuzzy sets such as type-2 fuzzy sets, intuitionistic fuzzy sets, hesitant fuzzy sets, Pythagorean fuzzy sets, and neutrosophic sets. One of the first ordinary fuzzy AHP models is Buckley’s fuzzy AHP. A Z-fuzzy number is a combined expression of a restriction function (RF) and a reliability function of RF. We propose a Z-number based fuzzy AHP. We also present an illustrative example.

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Author information

Authors and Affiliations

  1. Istanbul Gelisim University, 34310, Avcilar, Istanbul, Turkey

    Nurdan Yildiz

  2. Istanbul Technical University, 34367, Besiktas, Istanbul, Turkey

    Cengiz Kahraman

Authors
  1. Nurdan Yildiz
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  2. Cengiz Kahraman
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Corresponding author

Correspondence to Nurdan Yildiz .

Editor information

Editors and Affiliations

  1. Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Industrial Engineering Department, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  3. Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Sezi Cevik Onar

  4. Management Faculty, Istanbul Technical University, İstanbul, Turkey

    Basar Oztaysi

  5. Industrial Engineering Department, Galatasaray University, Istanbul, Turkey

    A. Cagri Tolga

  6. Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Irem Ucal Sari

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Yildiz, N., Kahraman, C. (2020). Evaluation of Social Sustainable Development Factors Using Buckley’s Fuzzy AHP Based on Z-Numbers. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_92

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