Intelligent Systems and Soft Computing Prospects Tools and Applications 1804 Lecture Notes in Computer Science 1st edition by Lotfi Zadeh, Benham Azvine, Detlef Nauck, Nader Azarmi ISBN 3540678379 978-3540678373
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Authors:Intelligent Systems; Soft Computing , Author sort:Systems, Intelligent & Computing, Soft , Published:Published:Mar 2008
Intelligent Systems and Soft Computing: Prospects, Tools and Applications: 1804 Lecture Notes in Computer Science 1st edition by Lotfi Zadeh, Benham Azvine, Detlef Nauck, Nader Azarmi – Ebook PDF Instant Download/Delivery. 3540678379 978-3540678373
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ISBN 10: 3540678379
ISBN 13: 978-3540678373
Author: Lotfi Zadeh, Benham Azvine, Detlef Nauck, Nader Azarmi
Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. The papers in this book explore the possibility of bringing these two areas together.
This book is unique in the way it concentrates on building intelligent software systems by combining methods from diverse disciplines, such as fuzzy set theory, neuroscience, agent technology, knowledge discovery, and symbolic artificial intelligence. The first part of the book focuses on foundational aspects and future directions; the second part provides the reader with an overview of recently developed software tools for building flexible intelligent systems; the final section studies developed applications in various fields.
Intelligent Systems and Soft Computing: Prospects, Tools and Applications: 1804 Lecture Notes in Computer Science 1st Table of contents:
Preface
- Overview of Intelligent Systems
- Introduction to Soft Computing
- Scope and Applications of the Book
- Structure of the Volume
Chapter 1: Introduction to Intelligent Systems
- Defining Intelligent Systems
- Key Characteristics and Components of Intelligent Systems
- The Role of Artificial Intelligence and Machine Learning
- Overview of Soft Computing Techniques
Chapter 2: Soft Computing and its Components
- Neural Networks
- Fuzzy Logic Systems
- Evolutionary Computing (Genetic Algorithms)
- Swarm Intelligence (Ant Colony Optimization, Particle Swarm Optimization)
- Hybrid Soft Computing Approaches
Chapter 3: Techniques and Tools in Soft Computing
- Neural Network Tools and Frameworks
- Fuzzy Logic Tools
- Evolutionary Algorithms in Practice
- Tools for Swarm Intelligence Algorithms
- Integrated Soft Computing Environments
Chapter 4: Machine Learning and Pattern Recognition
- Supervised and Unsupervised Learning Algorithms
- Classification, Regression, and Clustering
- Pattern Recognition in Intelligent Systems
- Applications in Image and Speech Recognition
- Real-World Case Studies
Chapter 5: Optimization Techniques in Soft Computing
- Problem Formulation and Optimization Methods
- Metaheuristic Algorithms for Optimization
- Multi-Objective Optimization in Soft Computing
- Applications in Industrial and Engineering Domains
Chapter 6: Fuzzy Logic and its Applications
- Basics of Fuzzy Logic Systems
- Fuzzy Control Systems
- Fuzzy Clustering and Decision Making
- Applications in Control Systems, Robotics, and Decision Support
Chapter 7: Evolutionary Algorithms and Their Applications
- Overview of Genetic Algorithms (GAs)
- Differential Evolution and Genetic Programming
- Applications in Engineering, Finance, and Healthcare
- Case Studies on Evolutionary Algorithms in Problem Solving
Chapter 8: Hybrid Intelligent Systems
- Combining Soft Computing Techniques for Enhanced Performance
- Fuzzy-Genetic Hybrid Systems
- Neural-Fuzzy Systems and Applications
- Evolutionary Neural Networks and Hybrid Optimization
- Real-World Hybrid Systems Applications
Chapter 9: Intelligent Systems in Practice
- Autonomous Systems and Robotics
- Intelligent Transportation Systems
- Artificial Neural Networks in Finance
- Applications in Healthcare and Medical Diagnosis
- Industrial Automation and Smart Systems
Chapter 10: Future Directions in Intelligent Systems and Soft Computing
- Emerging Trends in Soft Computing
- Challenges in Implementing Intelligent Systems
- The Role of Big Data and Cloud Computing in Intelligent Systems
- Ethical Considerations and Future Prospects
Appendices
- Mathematical Foundations of Soft Computing
- Glossary of Terms
- Tools and Resources for Further Learning
Index
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