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The 2-tuple Linguistic Model

Computing with Words in Decision Making

  • Book
  • © 2015

Overview

Authors:
  1. Luis Martínez

    1. Dept. Computer Science, University of Jaen, Jaen, Spain

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  2. Rosa M. Rodriguez

    1. Department of Computer Science and AI, University of Granada, Granada, Spain

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  3. Francisco Herrera

    1. Department of Computer Science and AI, University of Granada, Granada, Spain

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  • Provides a detailed overview of the 2-tuple fuzzy linguistic representation and its extensions
  • Introduces the software FLINTSTONES that provides tools for solving linguistic decision problems based on the 2-tuple linguistic model
  • Includes a compendium of applications where the 2-tuple fuzzy linguistic model has been used and how it can inspire other future applications in very different fields

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Linguistic Decision Making and Computing with Words

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 1-21

  3. 2-Tuple Linguistic Model

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 23-42

  4. Linguistic Approaches Based on the 2-Tuple Fuzzy Linguistic Representation Model

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 43-50

  5. Decision Making in Heterogeneous Context: 2-Tuple Linguistic Based Approaches

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 51-82

  6. Decision Making with Unbalanced Linguistic Information

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 83-112

  7. Dealing with Hesitant Fuzzy Linguistic Information in Decision Making

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 113-129

  8. 2-Tuple Linguistic Decision Based Applications

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 131-143

  9. Flintstones: A Fuzzy Linguistic Decision Tools Enhancement Suite

    • Luis Martínez, Rosa M. Rodriguez, Francisco Herrera
    Pages 145-168
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Keywords

About this book

This book examines one of the more common and wide-spread methodologies to deal with uncertainty in real-world decision making problems, the computing with words paradigm, and the fuzzy linguistic approach. The 2-tuple linguistic model is the most popular methodology for computing with words (CWW), because it improves the accuracy of the linguistic computations and keeps the interpretability of the results.

The authors provide a thorough review of the specialized literature in CWW and highlight the rapid growth and applicability of the 2-tuple linguistic model. They explore the foundations and methodologies for CWW in complex frameworks and extensions. The book introduces the software FLINTSTONES that provides tools for solving linguistic decision problems based on the 2-tuple linguistic model.

Professionals and researchers working in the field of classification or fuzzy sets and systems will find The 2-tuple Linguistic Model: Computing with Words in Decision Making a valuable resource. Undergraduate and postdoctoral students studying computer science and statistics will also find this book a useful study guide.

Authors and Affiliations

  • Dept. Computer Science, University of Jaen, Jaen, Spain

    Luis Martínez

  • Department of Computer Science and AI, University of Granada, Granada, Spain

    Rosa M. Rodriguez, Francisco Herrera

Bibliographic Information

  • Book Title: The 2-tuple Linguistic Model

  • Book Subtitle: Computing with Words in Decision Making

  • Authors: Luis Martínez, Rosa M. Rodriguez, Francisco Herrera

  • DOI: https://doi.org/10.1007/978-3-319-24714-4

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing Switzerland 2015

  • Hardcover ISBN: 978-3-319-24712-0Published: 18 December 2015

  • Softcover ISBN: 978-3-319-79665-9Published: 21 March 2019

  • eBook ISBN: 978-3-319-24714-4Published: 09 December 2015

  • Edition Number: 1

  • Number of Pages: XIII, 168

  • Number of Illustrations: 17 b/w illustrations, 18 illustrations in colour

  • Topics: Natural Language Processing (NLP), Logics and Meanings of Programs

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