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Fuzzy Logic in Intelligent System Design

Theory and Applications

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Patricia Melin

    1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

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  2. Oscar Castillo

    1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

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  3. Janusz Kacprzyk

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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  4. Marek Reformat

    1. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

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  5. William Melek

    1. Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Canada

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  • Describes recent advances in the use of fuzzy logic for the design of hybrid intelligent systems based on nature-inspired optimization and their applications in diverse areas
  • Addresses areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems
  • Based on papers presented at the North American Fuzzy Information Processing Society Annual Conference (NAFIPS 2017) held from 16 to 18 October 2017 in Cancun, Mexico
  • Highlights recent research on Fuzzy Logic in Intelligent System Design

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 648)

Included in the following conference series:

Conference proceedings info: NAFIPS 2017.

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Table of contents (45 papers)

  1. Front Matter

    Pages i-xi
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  2. Theoretical Aspects of Fuzzy Logic

    1. Front Matter

      Pages 1-1
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    2. Can Multi-constraint Fuzzy Optimization Bring Complex Problems in Selecting Optimal Solar Power Generating System into Focus?

      • Akash Dand, Chetankumar Patil, Ashok Deshpande
      Pages 3-8

    3. Relating Fuzzy Set Similarity Measures

      • Valerie Cross
      Pages 9-21

    4. Correlation Measures for Bipolar Rating Profiles

      • Fernando Monroy-Tenorio, Ildar Batyrshin, Alexander Gelbukh, Valery Solovyev, Nailya Kubysheva, Imre Rudas
      Pages 22-32

    5. Solving Real-World Fuzzy Quadratic Programming Problems by Dual Parametric Approach

      • Ricardo Coelho
      Pages 33-38

  3. Type-2 Fuzzy Logic

    1. Front Matter

      Pages 39-39
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    2. A Type-2 Fuzzy Hybrid Expert System for Commercial Burglary

      • M. H. Fazel Zarandi, A. Seifi, H. Esmaeeli, Sh. Sotudian
      Pages 41-51

    3. A Type-2 Fuzzy Expert System for Diagnosis of Leukemia

      • Ali Akbar Sadat Asl, Mohammad Hossein Fazel Zarandi
      Pages 52-60

    4. Comparative Study of Metrics That Affect in the Performance of the Bee Colony Optimization Algorithm Through Interval Type-2 Fuzzy Logic Systems

      • Leticia Amador-Angulo, Oscar Castillo
      Pages 61-72

    5. Type-2 Fuzzy Approach in Multi Attribute Group Decision Making Problem

      • Zohre Moattar Husseini, Mohammad Hossein Fazel Zarandi
      Pages 73-81

  4. Fuzzy Logic in Metaheuristics

    1. Front Matter

      Pages 83-83
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    2. A New Approach for Dynamic Mutation Parameter in the Differential Evolution Algorithm Using Fuzzy Logic

      • Patricia Ochoa, Oscar Castillo, José Soria
      Pages 85-93

    3. Study on the Use of Type-1 and Interval Type-2 Fuzzy Systems Applied to Benchmark Functions Using the Fuzzy Harmony Search Algorithm

      • Cinthia Peraza, Fevrier Valdez, Oscar Castillo
      Pages 94-103

    4. Fuzzy Adaptation for Particle Swarm Optimization for Modular Neural Networks Applied to Iris Recognition

      • Daniela Sánchez, Patricia Melin, Oscar Castillo
      Pages 104-114

    5. A New Metaheuristic Based on the Self-defense Mechanisms of the Plants with a Fuzzy Approach Applied to the CEC2015 Functions

      • Camilo Caraveo, Fevrier Valdez, Oscar Castillo
      Pages 115-121

    6. Fuzzy Chemical Reaction Algorithm with Dynamic Adaptation of Parameters

      • David de la O, Oscar Castillo, Leslie Astudillo, Jose Soria
      Pages 122-130

    7. Methodology for the Optimization of a Fuzzy Controller Using a Bio-inspired Algorithm

      • Marylu L. Lagunes, Oscar Castillo, Jose Soria
      Pages 131-137

  5. Emergent Intelligent Models

    1. Front Matter

      Pages 139-139
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    2. Cellular Automata Enhanced Quantum Inspired Edge Detection

      • Yoshio Rubio, Oscar Montiel, Roberto Sepúlveda
      Pages 141-146
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  1. Fuzzy Logic in Intelligent System Design

Keywords

About this book

This book describes recent advances in the use of fuzzy logic for the design of hybrid intelligent systems based on nature-inspired optimization and their applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Based on papers presented at the North American Fuzzy Information Processing Society Annual Conference (NAFIPS 2017), held in Cancun, Mexico from 16 to 18 October 2017, the book is divided into nine main parts, the first of which first addresses theoretical aspects, and proposes new concepts and algorithms based on type-1 fuzzy systems. The second part consists of papers on new concepts and algorithms for type-2 fuzzy systems, and on applications of type-2 fuzzy systems in diverse areas, such as time series prediction and pattern recognition. In turn, the third part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques describing newnature-inspired optimization algorithms that use fuzzy dynamic adaptation of parameters. The fourth part presents emergent intelligent models, which range from quantum algorithms to cellular automata. The fifth part explores applications of fuzzy logic in diverse areas of medicine, such as the diagnosis of hypertension and heart diseases. The sixth part describes new computational intelligence algorithms and their applications in different areas of intelligent control, while the seventh examines the use of fuzzy logic in different mathematic models. The eight part deals with a diverse range of applications of fuzzy logic, ranging from environmental to autonomous navigation, while the ninth covers theoretical concepts of fuzzy models

Editors and Affiliations

  • Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Patricia Melin, Oscar Castillo

  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  • Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

    Marek Reformat

  • Laboratory of Computational Intelligence and Automation, University of Waterloo, Waterloo, Canada

    William Melek

Bibliographic Information

  • Book Title: Fuzzy Logic in Intelligent System Design

  • Book Subtitle: Theory and Applications

  • Editors: Patricia Melin, Oscar Castillo, Janusz Kacprzyk, Marek Reformat, William Melek

  • Series Title: Advances in Intelligent Systems and Computing

  • DOI: https://doi.org/10.1007/978-3-319-67137-6

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2018

  • Softcover ISBN: 978-3-319-67136-9Published: 30 September 2017

  • eBook ISBN: 978-3-319-67137-6Published: 30 September 2017

  • Series ISSN: 2194-5357

  • Series E-ISSN: 2194-5365

  • Edition Number: 1

  • Number of Pages: XI, 422

  • Number of Illustrations: 140 b/w illustrations

  • Topics: Computational Intelligence, Artificial Intelligence

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