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Intelligent and Fuzzy Systems

Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 1

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Cengiz Kahraman

    1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Türkiye

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  2. Sezi Cevik Onar

    1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Türkiye

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  3. Selcuk Cebi

    1. Department of Industrial Engineering, Yildiz Technical University, Besiktas, Türkiye

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  4. Basar Oztaysi

    1. Department of Industrial Engineering, Istanbul Technical University, Besiktas, Türkiye

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  5. A. Cagrı Tolga

    1. Department of Industrial Engineering, Galatasaray University, Istanbul, Türkiye

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  6. Irem Ucal Sari

    1. Department of Industrial Engineering, Istanbul Technical University, Besiktas, Türkiye

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  • Presents recent research in Intelligent and Fuzzy Techniques
  • Covers proceedings of the Intelligent and Fuzzy Techniques INFUS 2024 Conference
  • Provides interdisciplinary research between fuzzy and intelligent systems and real complex systems

Part of the book series: Lecture Notes in Networks and Systems (LNNS, volume 1088)

Included in the following conference series:

Conference proceedings info: INFUS 2024.

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About this book

This book presents recent research in intelligent and fuzzy techniques on Intelligent Industrial Informatics and Efficient Networks. This cutting-edge field integrates advanced technologies, such as artificial intelligence, machine learning and data analytics, into industrial processes, revolutionizing the way industries operate. The book presents the examples of the implementation of smart sensors and IoT devices, which facilitate real-time data collection and communication. High-speed, low-latency networks ensure that information flows effortlessly between devices, enabling timely responses and enabling the coordination of complex manufacturing processes. This network architecture supports the integration of edge computing, where data processing occurs closer to the source, reducing latency and enabling faster decision-making. The readers can benefit from this book for maintaining a leadership position among competitors in both manufacturing and service companies. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc. and Ph.D. students studying intelligent and fuzzy techniques. The book covers fuzzy logic theory and applications, heuristics and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.

Keywords

Table of contents (84 papers)

  1. Front Matter

    Pages i-xvii
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  3. Fuzzy MCDM Theory and Applications

    1. Front Matter

      Pages 35-35
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    2. Fuzzy Performance Measurement: A Literature Review

      • Basar Oztaysi, Sezi CevikOnar, Selcuk Cebi, Cengiz Kahraman
      Pages 37-43

    3. Evaluation of Business Intelligence Tools for the Logistics Sector with Hesitant Fuzzy Hybrid MCDM Methods

      • Eyüp Tolunay Küp, Burcu Demir, Alper Gün, Funda Samanlioglu, Şevval Ece Gençay, Gökçenur Koçak
      Pages 44-60

    4. Investigating Smart City Applications: A Case Study from İstanbul

      • Mehmet Ali Taş, S. Emre Alptekin
      Pages 61-69

    5. Fermatean Fuzzy TOPSIS Method Based on Prospect Theory

      • Mu Zhang, Meng-yao Zhan
      Pages 70-81

    6. New Multi Criteria Decision Making Methodology EFEE Under Uncertainty on Paris City Micromobility

      • Esra Çakır, Çağrı Tolga
      Pages 82-90

    7. Threshold Aggregation of Fuzzy Data Using Fuzzy Cardinalities of a Set of Fuzzy Estimates

      • Alexander Lepskiy
      Pages 91-98

    8. A Collaborative Decision-Making Framework in Humanitarian Logistics

      • Gülçin Büyüközkan, Fethullah Göçer
      Pages 99-107

    9. Integrating Fuzzy AHP and TOPSIS for Optimal Air Fryer Selection: A Consumer-Centric Approach

      • Mert Paldrak, Fatma Neşe Özen, Berkin Yeginoğlu, Cansu Bora, Armağan Yağız Terim
      Pages 108-119

    10. A Comparative Analysis of Classical AHP, Fuzzy AHP, and Z-Fuzzy AHP Methods for Flood Risk Assessment in Büyükçekmece District

      • Gülşah Kılıç, Oğuz Altıntaş
      Pages 120-127

    11. Fuzzy Evaluation of Stakeholders’ Aspects in Water Resources Management

      • Thomas Bakas, Christopher Papadopoulos, Mike Spiliotis, Basil Papadopoulos
      Pages 128-136

    12. Sustainability Performance Evaluation in Faculties: A COPRAS-Based Assessment

      • Sezin Güleryüz
      Pages 137-146

  4. Artificial Intelligence

    1. Front Matter

      Pages 147-147
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Other volumes

  1. Intelligent and Fuzzy Systems

  2. Intelligent and Fuzzy Systems

  3. Intelligent and Fuzzy Systems

Editors and Affiliations

  • Department of Industrial Engineering, Istanbul Technical University, Istanbul, Türkiye

    Cengiz Kahraman, Sezi Cevik Onar

  • Department of Industrial Engineering, Yildiz Technical University, Besiktas, Türkiye

    Selcuk Cebi

  • Department of Industrial Engineering, Istanbul Technical University, Besiktas, Türkiye

    Basar Oztaysi, Irem Ucal Sari

  • Department of Industrial Engineering, Galatasaray University, Istanbul, Türkiye

    A. Cagrı Tolga

Bibliographic Information

  • Book Title: Intelligent and Fuzzy Systems

  • Book Subtitle: Intelligent Industrial Informatics and Efficient Networks Proceedings of the INFUS 2024 Conference, Volume 1

  • Editors: Cengiz Kahraman, Sezi Cevik Onar, Selcuk Cebi, Basar Oztaysi, A. Cagrı Tolga, Irem Ucal Sari

  • Series Title: Lecture Notes in Networks and Systems

  • DOI: https://doi.org/10.1007/978-3-031-70018-7

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

  • Softcover ISBN: 978-3-031-70017-0Published: 02 September 2024

  • eBook ISBN: 978-3-031-70018-7Published: 01 September 2024

  • Series ISSN: 2367-3370

  • Series E-ISSN: 2367-3389

  • Edition Number: 1

  • Number of Pages: XVII, 785

  • Number of Illustrations: 161 b/w illustrations, 132 illustrations in colour

  • Topics: Computational Intelligence, Data Engineering, Artificial Intelligence

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