Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

1. Front Matter

   Pages i-xi

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2. Type-2 Fuzzy Logic in Metaheuristics

   1. Front Matter

      Pages 1-1

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   2. A Comparative Study of Dynamic Adaptation of Parameters in the GWO Algorithm Using Type-1 and Interval Type-2 Fuzzy Logic

      • Luis Rodríguez, Oscar Castillo, Mario García, José Soria

      Pages 3-16

   3. Ensemble Neural Network Optimization Using a Gravitational Search Algorithm with Interval Type-1 and Type-2 Fuzzy Parameter Adaptation in Pattern Recognition Applications

      • Beatriz González, Patricia Melin, Fevrier Valdez, German Prado-Arechiga

      Pages 17-27

   4. Improved Method Based on Type-2 Fuzzy Logic for the Adaptive Harmony Search Algorithm

      • Cinthia Peraza, Fevrier Valdez, Oscar Castillo

      Pages 29-37

   5. Comparison of Bio-Inspired Methods with Parameter Adaptation Through Interval Type-2 Fuzzy Logic

      • Frumen Olivas, Fevrier Valdez, Oscar Castillo

      Pages 39-53

   6. Differential Evolution Algorithm with Interval Type-2 Fuzzy Logic for the Optimization of the Mutation Parameter

      • Patricia Ochoa, Oscar Castillo, José Soria

      Pages 55-65

3. Neural Networks Theory and Applications

   1. Front Matter

      Pages 67-67

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   2. Person Recognition with Modular Deep Neural Network Using the Iris Biometric Measure

      • Fernando Gaxiola, Patricia Melin, Fevrier Valdez, Juan Ramón Castro

      Pages 69-80

   3. Neuro-evolutionary Neural Network for the Estimation of Melting Point of Ionic Liquids

      • Jorge A. Cerecedo-Cordoba, Juan Javier González Barbosa, J. David Terán-Villanueva, Juan Frausto-Solís

      Pages 81-88

   4. A Proposal to Classify Ways of Walking Patterns Using Spiking Neural Networks

      • Karen Fabiola Mares, Rosario Baltazar, Miguel Ángel Casillas, Víctor Zamudio, Lenin Lemus

      Pages 89-98

   5. Partially-Connected Artificial Neural Networks Developed by Grammatical Evolution for Pattern Recognition Problems

      • Olga Quiroz-Ramírez, Andrés Espinal, Manuel Ornelas-Rodríguez, Alfonso Rojas-Domínguez, Daniela Sánchez, Héctor Puga-Soberanes et al.

      Pages 99-112

4. Metaheuristics: Theory and Applications

   1. Front Matter

      Pages 113-113

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   2. Bio-inspired Metaheuristics for Hyper-parameter Tuning of Support Vector Machine Classifiers

      • Adán Godínez-Bautista, Luis Carlos Padierna, Alfonso Rojas-Domínguez, Héctor Puga, Martín Carpio

      Pages 115-130

   3. Galactic Swarm Optimization with Adaptation of Parameters Using Fuzzy Logic for the Optimization of Mathematical Functions

      • Emer Bernal, Oscar Castillo, José Soria, Fevrier Valdez

      Pages 131-140

   4. Protein Folding Problem in the Case of Peptides Solved by Hybrid Simulated Annealing Algorithms

      • Anylu Melo-Vega, Juan Frausto-Solís, Guadalupe Castilla-Valdez, Ernesto Liñán-García, Juan Javier González-Barbosa, David Terán-Villanueva

      Pages 141-152

   5. Optimization of the Parameters of Smoothed Particle Hydrodynamics Method, Using Evolutionary Algorithms

      • Juan de Anda-Suárez, Martín Carpio, Solai Jeyakumar, Héctor José Puga-Soberanes, Juan F. Mosiño, Laura Cruz-Reyes

      Pages 153-167

   6. Symbolic Regression by Means of Grammatical Evolution with Estimation Distribution Algorithms as Search Engine

      • M. A. Sotelo-Figueroa, Arturo Hernández-Aguirre, Andrés Espinal, J. A. Soria-Alcaraz, Janet Ortiz-López

      Pages 169-177

5. Fuzzy Control

   1. Front Matter

      Pages 179-179

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   2. Impact Study of the Footprint of Uncertainty in Control Applications Based on Interval Type-2 Fuzzy Logic Controllers

      • Emanuel Ontiveros, Patricia Melin, Oscar Castillo

      Pages 181-197

This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book is organized into seven main parts, each with a collection of papers on a similar subject. The first part presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory and applications, and includes papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The third part addresses the theory and practice of meta-heuristics in different areas of application, while the fourth part describes diverse fuzzy logic applications in the control area, which can be considered as intelligent controllers. The next two parts explore applications in areas, such as time series prediction, and pattern recognition and new optimization and evolutionary algorithms and their applications respectively. Lastly, the seventh part addresses the design and application of different hybrid intelligent systems.

• Type-2 Fuzzy Logic in Metaheuristics
• Neural Networks Metaheuristics
• Fuzzy Control
• Fuzzy Logic
• Optimization and Evolutionary Algorithms
• Hybrid Intelligent Systems

“The book may be useful for scholars trying to identify research topics related to areas such as fuzzy logic, neural networks, and optimization. Many interesting real-world applications greatly enhance the utility of the book. The editors have done a good job of bringing related topics together under various headings.” (S. V. Nagaraj, Computing Reviews, January, 2019)

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

  Oscar Castillo

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

  Patricia Melin

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

  Janusz Kacprzyk

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