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Fuzzy Intelligent Systems

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Approximate reasoning in medical expert systems
Autonomous fuzzy expert system for tactical communications networks
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Chapter 4: Fuzzy associative memories
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Fuzzy expert systems
Fuzzy linguistic inference network generator
Fuzzy-Filtered Neural Networks
Genetic Fuzzy Neural Network
Genetic Fuzzy Rule-Based Systems Based on the Iterative Rule Learning Approach
Genetic Fuzzy Rule-Based Systems Based on the Michigan Approach
Genetic Fuzzy Rule-Based Systems Based on the Pittsburgh Approach
Genetic Fuzzy Rule-Based Systems Based System Paradigms
Genetic Tuning Process
Hybrid Configurations
Hybrid Learning System
Hybrid Neuro Fuzzy Models
Learning with Genetic Algorithm
Modeling with Hybrid neuro-fuzzy systems
Multiobjective Evolutionary Fuzzy Systems Designed for Fuzzy Association Rule Mining
Multiobjective Evolutionary Fuzzy Systems Designed for Multiobjective Control Problems
Neural-Network-Based Fuzzy Systems
New Trends in Multiobjective Evolutionary Fuzzy Systems
Processing imperfect information using structured frameworks
Recurrent neuro-fuzzy systems

Product details

  • ISBN 9781119760450
  • Weight: 454g
  • Dimensions: 10 x 10mm
  • Publication Date: 05 Nov 2021
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description
FUZZY INTELLIGENT SYSTEMS

A comprehensive guide to Expert Systems and Fuzzy Logic that is the backbone of artificial intelligence.

The objective in writing the book is to foster advancements in the field and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and those in education and research covering a broad cross section of technical disciplines.

Fuzzy Intelligent Systems: Methodologies, Techniques, and Applications comprises state-of-the-art chapters detailing how expert systems are built and how the fuzzy logic resembling human reasoning, powers them. Engineers, both current and future, need systematic training in the analytic theory and rigorous design of fuzzy control systems to keep up with and advance the rapidly evolving field of applied control technologies. As a consequence, expert systems with fuzzy logic capabilities make for a more versatile and innovative handling of problems. This book showcases the combination of fuzzy logic and neural networks known as a neuro-fuzzy system, which results in a hybrid intelligent system by combining a human-like reasoning style of neural networks.

Audience

Researchers and students in computer science, Internet of Things, artificial intelligence, machine learning, big data analytics and information and communication technology-related fields. Students will gain a thorough understanding of fuzzy control systems theory by mastering its contents.
About

E. Chandresekaran, PhD is a Professor of Mathematics at Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai India.

R. Anandan, PhD is a IBMS/390 Mainframe professional, a Chartered Engineer from the Institution of Engineers in India and received a fellowship from Bose Science Society, India. He is currently a Professor in the Department of Computer Science and Engineering, School of Engineering, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai.

G. Suseendran, PhD was an assistant professor in the Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai and passed away as this book was being prepared.

S. Balamurugan, PhD is the Director of Research and Development, Intelligent Research Consultancy Services(iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India(RESI), India.

Hanaa Hachimi, PhD is an associate professor at the Ibn Tofail University, in the National School of Applied Sciences ENSA in Kenitra, Morocco. She is President of the Moroccan Society of Engineering Sciences and Technology (MSEST).