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© 2016

Imprecision and Uncertainty in Information Representation and Processing

New Tools Based on Intuitionistic Fuzzy Sets and Generalized Nets

  • Plamen Angelov
  • Sotir Sotirov

Benefits

  • Offers a snapshot of the state-of-the-art in the applications of intuitionistic fuzzy sets and generalized nets

  • Provides readers with a concise yet comprehensive overview of the underlying mathematical concepts

  • Discusses relevant examples and case studies

Book

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 332)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Perspectives in Intuitionistic Fuzzy Set

  3. Intuitionistic Fuzzy Set

  4. Generalized Nets

    1. Front Matter
      Pages 273-273

About this book

Introduction

The book offers a comprehensive and timely overview of advanced mathematical tools for both uncertainty analysis and modeling of parallel processes, with a special emphasis on intuitionistic fuzzy sets and generalized nets. The different chapters, written by active researchers in their respective areas, are structured to provide a coherent picture of this interdisciplinary yet still evolving field of science. They describe key tools and give practical insights into and research perspectives on the use of Atanassov's intuitionistic fuzzy sets and logic, and generalized nets for describing and dealing with uncertainty in different areas of science, technology and business, in a single, to date unique book. Here, readers find theoretical chapters, dealing with intuitionistic fuzzy operators, membership functions and algorithms, among other topics, as well as application-oriented chapters, reporting on the implementation of methods and relevant case studies in management science, the IT industry, medicine and/or education. With this book, the editors wish to pay homage to Professor Krassimir Todorov Atanassov for his pioneering work on both generalized nets and intuitionistic fuzzy set.

Keywords

Atanassov's Intuitionistic Fuzzy Sets Intuitionistic Fuzzy Relations Intuitionistic Fuzzy Topology Interval-valued Fuzzy Sets Construction of t-norms Ensemble Neural Networks Imbalanced Data Fuzzy Classifiers Differential Evolution Algorithm Algorithms for Transition Functioning

Editors and affiliations

  • Plamen Angelov
    • 1
  • Sotir Sotirov
    • 2
  1. 1.School of Computing and CommunicationsLancaster University BailriggLancasterUnited Kingdom
  2. 2.Intelligent Systems LaboratoryProf. Assen Zlatarov UniversityBourgasBulgaria

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