Fuzzy Logic in Intelligent System Design

1. Emergent Intelligent Models

   1. Competitive Hybrid Ensemble Using Neural Network and Decision Tree

      • Davin Kaing, Larry Medsker

      Pages 147-155

   2. Speeding Up Quantum Genetic Algorithms in Matlab Through the Quack_GPU V1

      • Oscar Montiel, Roberto Sepúlveda, Yoshio Rubio

      Pages 156-161

   3. Evolving Granular Fuzzy Min-Max Regression

      • Alisson Porto, Fernando Gomide

      Pages 162-171

   4. Optimization of Deep Neural Network for Recognition with Human Iris Biometric Measure

      • Fernando Gaxiola, Patricia Melin, Fevrier Valdez, Juan R. Castro

      Pages 172-180

   5. Dynamic Local Trend Associations in Analysis of Comovements of Financial Time Series

      • Francisco Javier García-López, Ildar Batyrshin, Alexander Gelbukh

      Pages 181-188

2. Fuzzy Logic in Medicine

   1. Front Matter

      Pages 189-189

      PDF

   2. An Expert System Based on Fuzzy Bayesian Network for Heart Disease Diagnosis

      • M. H. Fazel Zarandi, A. Seifi, M. M. Ershadi, H. Esmaeeli

      Pages 191-201

   3. A Hybrid Intelligent System Model for Hypertension Risk Diagnosis

      • Ivette Miramontes, Gabriela Martínez, Patricia Melin, German Prado-Arechiga

      Pages 202-213

   4. Estimation of Population Pharmacokinetic Model Parameters Using a Genetic Algorithm

      • Carlos Sepúlveda, Oscar Montiel, José M. Cornejo, Roberto Sepúlveda

      Pages 214-221

3. Intelligent Control

   1. Front Matter

      Pages 223-223

      PDF

   2. Outdoor Robot Navigation Based on Particle Swarm Optimization

      • Erasmo Gabriel Martínez Soltero, Carlos Lopéz-Franco, Alma Y. Alanis, Nancy Arana-Daniel

      Pages 225-231

   3. Trajectory Optimization for an Autonomous Mobile Robot Using the Bat Algorithm

      • Jonathan Perez, Patricia Melin, Oscar Castillo, Fevrier Valdez, Claudia Gonzalez, Gabriela Martinez

      Pages 232-241

   4. Neural Identifier-Control Scheme for Nonlinear Discrete Systems with Input Delay

      • Jorge D. Rios, Alma Y. Alanís, Nancy Arana-Daniel, Carlos López-Franco

      Pages 242-247

   5. An Application of Neural Network to Heavy Oil Distillation with Recognitions with Intuitionistic Fuzzy Estimation

      • Sotir Sotirov, Evdokia Sotirova, Dicho Stratiev, Danail Stratiev, Nikolay Sotirov

      Pages 248-255

   6. PID Implemented by a Type-1 Fuzzy Logic System with Back-Propagation Algorithm for Online Tuning of Its Gains

      • Alberto Álvarez, David Reyes, Ernesto J. Rincón, José Valderrama, Pascual Noradino, Gerardo M. Méndez

      Pages 256-263

   7. A PID Using a Non-singleton Fuzzy Logic System Type 1 to Control a Second-Order System

      • David Reyes, Alberto Álvarez, Ernesto J. Rincón, José Valderrama, Pascual Noradino, Gerardo M. Méndez

      Pages 264-269

   8. Fuzzy Multi-Criteria Decision Making and Fuzzy Information Gain Based Automotive Recommender System

      • Charu Gupta, Amita Jain

      Pages 270-277

4. Fuzzy Logic in Mathematics

   1. Front Matter

      Pages 279-279

      PDF

   2. The Shape of the Optimal Value of a Fuzzy Linear Programming Problem

      • Milan Hladík, Michal Černý

      Pages 281-286

   3. How to Gauge the Accuracy of Fuzzy Control Recommendations: A Simple Idea

      • Patricia Melin, Oscar Castillo, Andrzej Pownuk, Olga Kosheleva, Vladik Kreinovich

      Pages 287-292

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

• Intelligent Systems
• Fuzzy Logic
• Intelligent System Design
• Hybrid Intelligent Systems
• NAFIPS 2017

• 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

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