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Title Details:
Fundamentals of Computational Intelligence
Other Titles: Fuzzy, Neural and Evolutionary Computing: An Approach to Machine Intelligence
Authors: Dounis, Anastasios
Subject: HUMANITIES AND ARTS > LOGIC AND PHILOSOPHY OF LOGIC > LOGICS > NONCLASSICAL LOGICS > FUZZY LOGIC
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS > BASIC MACHINE LEARNING
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS > REASONING UNDER UNCERTAINTY
NATURAL SCIENCES AND AGRICULTURAL SCIENCES > PHYSICS > INDERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY > RENEWABLE ENERGY RESOURCES AND APPLICATIONS
MEDICINE AND HEALTH SCIENCES, LIFE SCIENCES, BIOLOGICAL SCIENCES > HEALTH SCIENCES > BIOMEDICAL ENGINEERING
ENGINEERING AND TECHNOLOGY > TECHNOLOGICAL SCIENCES AND ENGINEERING > INSTRUMENTATION TECHNOLOGY AND ENGINEERING > (AUTOMATIC) CONTROL ENGINEERING
LAW AND SOCIAL SCIENCES > ECONOMIC SCIENCES > MICROECONOMICS > INFORMATION, KNOWLEDGE, AND UNCERTAINTY
Keywords:
Fuzzy Computing
Uncertainty
Fuzzy Logic Systems
Extensions of Fuzzy Set
Neural Computing
Pattern Recognition with Artificial Neural Networks
Reinforcement Learning
Evolutionary Computing
Genetic Algorithms
Optimization of multiple objectives
Fuzzy Decision Logic
Hybrid Computational Intelligence Systems
Adaptive neuro fuzzy inference system
Intelligent Control
Supervisory Fuzzy Control
Extraction of Fuzzy Rules from Data
Evolutionary Fuzzy Logic Systems
Intelligent Time Series Prediction
Fuzzy Modeling
Fuzzy medical image processing
Intelligent medical diagnosis
Description:
Abstract:
The book "Fundamentals of Computational Intelligence: Fuzzy, Neural and Evolutionary Computation - An Approach to Machine Learning" is designed as an introductory textbook in Computational Intelligence and is addressed to students of higher education institutions, but also to those who are involved in related topics on a research or professional level. Artificial Intelligence (AI), which is a key branch of Computer Science, is evolving as a dominant technology of the future. The topics covered in the text comprehensively and extensively cover the scientific field of Computational Intelligence (CI). AI comprises three main branches of research and application: 1) Fuzzy Computation, which formulates models that approximate how people think and how people describe the world around them; 2) Neural Computation, which offers powerful models to approximate how the brain works and learns; and 3) Evolutionary Computation, which exploits biological and evolutionary models to search for optimal solutions to complex problems of excellence. The synergy of the above three disciplines has led to hybrid systems that collaborate, complement each other and provide optimal solutions to complex problems in Engineering and Science. The structure of the book is designed in a way that encourages self-learning. The textbook can be an introductory course, with a focus on intelligence technologies, for undergraduate and graduate students. The book is organized in five chapters, accompanied by an Appendix. The first three chapters are self-contained, learning entities, while the next two assume the basic knowledge of the previous three chapters. The fifth chapter complements the material of the first four chapters, where examples and applications of computational intelligence technologies are developed.
Linguistic Editors: Paxinou, Evgenia
Graphic Editors: Tsakmaki, Eleni
Type: Undergraduate textbook
Creation Date: 14-05-2024
Modification Date: 13-07-2024
Item Details:
ISBN 978-618-228-245-8
License: Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0)
DOI http://dx.doi.org/10.57713/kallipos-988
Handle http://hdl.handle.net/11419/13341
Bibliographic Reference: Dounis, A. (2024). Fundamentals of Computational Intelligence [Undergraduate textbook]. Kallipos, Open Academic Editions. https://dx.doi.org/10.57713/kallipos-988
Language: Greek
Consists of:
1. Fuzzy Computing
2. Neural Computing
3. Evolutionary Computing
4. Hybrid Computational Intelligence Systems
5. Computational Intelligence–Examples and Applications
Number of pages 660
Version: v. 1.2
Publication Origin: Kallipos, Open Academic Editions
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