Genetic Fuzzy Systems: Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases
eBook - PDF

Genetic Fuzzy Systems: Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases

Evolutionary Tuning and Learning of Fuzzy Knowledge Bases

  1. 488 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Genetic Fuzzy Systems: Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases

Evolutionary Tuning and Learning of Fuzzy Knowledge Bases

About this book

In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas.Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms.

Frequently asked questions

Yes, you can cancel anytime from the Subscription tab in your account settings on the Perlego website. Your subscription will stay active until the end of your current billing period. Learn how to cancel your subscription.
No, books cannot be downloaded as external files, such as PDFs, for use outside of Perlego. However, you can download books within the Perlego app for offline reading on mobile or tablet. Learn more here.
Perlego offers two plans: Essential and Complete
  • Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
  • Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Both plans are available with monthly, semester, or annual billing cycles.
We are an online textbook subscription service, where you can get access to an entire online library for less than the price of a single book per month. With over 1 million books across 1000+ topics, we’ve got you covered! Learn more here.
Look out for the read-aloud symbol on your next book to see if you can listen to it. The read-aloud tool reads text aloud for you, highlighting the text as it is being read. You can pause it, speed it up and slow it down. Learn more here.
Yes! You can use the Perlego app on both iOS or Android devices to read anytime, anywhere — even offline. Perfect for commutes or when you’re on the go.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Genetic Fuzzy Systems: Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases by Oscar Cordon, Francisco Herrera, Frank Hoffmann in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Contents
  2. Foreword
  3. Preface
  4. Chapter 1 Fuzzy Rule-Based Systems
  5. Chapter 2 Evolutionary Computation
  6. Chapter 3 Introduction to Genetic Fuzzy Systems
  7. Chapter 4 Genetic Tuning Processes
  8. Chapter 5 Learning with Genetic Algorithms
  9. Chapter 6 Genetic Fuzzy Rule-Based Systems Based on the Michigan Approach
  10. Chapter 7 Genetic Fuzzy Rule-Based Systems Based on the Pittsburgh Approach
  11. Chapter 8 Genetic Fuzzy Rule-Based Systems Based on the Iterative Rule Learning Approach
  12. Chapter 9 Other Genetic Fuzzy Rule-Based System Paradigms
  13. Chapter 10 Other Kinds of Evolutionary Fuzzy Systems
  14. Chapter 11 Applications
  15. Bibliography
  16. Acronyms
  17. Index