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Author: Andreas Geyer-Schulz
Publisher: Physica
ISBN:
Category : Business & Economics
Languages : en
Pages : 460
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Book Description
This book integrates fuzzy rule-languages with genetic algorithms, genetic programming, and classifier systems with the goal of obtaining fuzzy rule-based expert systems with learning capabilities. The main topics are first introduced by solving small problems, then a prototype implementation of the algorithm is explained, and last but not least the theoretical foundations are given. The second edition takes into account the rapid progress in the application of fuzzy genetic algorithms with a survey of recent developments in the field. The chapter on genetic programming has been revised. An exact uniform initialization algorithm replaces the heuristic presented in the first edition. A new method of abstraction, compound derivations, is introduced.
Author: Andreas Geyer-Schulz
Publisher: Physica
ISBN:
Category : Business & Economics
Languages : en
Pages : 460
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Book Description
This book integrates fuzzy rule-languages with genetic algorithms, genetic programming, and classifier systems with the goal of obtaining fuzzy rule-based expert systems with learning capabilities. The main topics are first introduced by solving small problems, then a prototype implementation of the algorithm is explained, and last but not least the theoretical foundations are given. The second edition takes into account the rapid progress in the application of fuzzy genetic algorithms with a survey of recent developments in the field. The chapter on genetic programming has been revised. An exact uniform initialization algorithm replaces the heuristic presented in the first edition. A new method of abstraction, compound derivations, is introduced.
Author: Jay Liebowitz
Publisher: CRC Press
ISBN: 0429612494
Category : Computers
Languages : en
Pages : 725
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Book Description
The Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia. The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.
Author: Oscar Cord¢n
Publisher: World Scientific
ISBN: 9789810240172
Category : Computers
Languages : en
Pages : 492
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Book Description
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.
Author: Fouad Sabry
Publisher: One Billion Knowledgeable
ISBN:
Category : Computers
Languages : en
Pages : 174
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Book Description
What Is Rule Based System A rule-based system is used to store and modify knowledge in order to understand information in a manner that is helpful in the field of computer science. Applications and research in the field of artificial intelligence frequently make use of it. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Rule-Based System Chapter 2: Expert System Chapter 3: Inference Engine Chapter 4: Production System in Computer Science Chapter 5: Fuzzy Logic Chapter 6: Artificial Neural Network Chapter 7: Genetic Algorithm Chapter 8: Rule-Based Machine Learning Chapter 9: Logic Programming Chapter 10: Lexical Analysis (II) Answering the public top questions about rule based system. (III) Real world examples for the usage of rule based system in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of rule based system' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of rule based system.
Author: Richard Forsyth
Publisher: Chapman & Hall
ISBN:
Category : Adaptive computing systems
Languages : en
Pages : 258
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Book Description
Inference; Knowledge engineering; Learning; Machine learning strategies; Adaptative learning systems; Automating knowledge acquisition; The knowledge industry.
Author: Da Ruan
Publisher: Springer Science & Business Media
ISBN: 1461561914
Category : Mathematics
Languages : en
Pages : 364
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Book Description
Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms is an organized edited collection of contributed chapters covering basic principles, methodologies, and applications of fuzzy systems, neural networks and genetic algorithms. All chapters are original contributions by leading researchers written exclusively for this volume. This book reviews important concepts and models, and focuses on specific methodologies common to fuzzy systems, neural networks and evolutionary computation. The emphasis is on development of cooperative models of hybrid systems. Included are applications related to intelligent data analysis, process analysis, intelligent adaptive information systems, systems identification, nonlinear systems, power and water system design, and many others. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms provides researchers and engineers with up-to-date coverage of new results, methodologies and applications for building intelligent systems capable of solving large-scale problems.
Author: Abraham Kandel
Publisher: CRC Press
ISBN: 9780849342974
Category : Computers
Languages : en
Pages : 344
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Book Description
Until recently, fuzzy logic was the intellectual plaything of a handful of researchers. Now it is being used to enhance the power of intelligent systems, as well as improve the performance and reduce the cost of intelligent and "smart" products appearing in the commercial market. Fuzzy Expert Systems focuses primarily on the theory of fuzzy expert systems and their applications in science and engineering. In doing so, it provides the first comprehensive study of "soft" expert systems and applications for those systems. Topics covered include general purpose fuzzy expert systems, processing imperfect information using structured frameworks, the fuzzy linguistic inference network generator, fuzzy associative memories, the role of approximate reasoning in medical expert systems, MILORD (a fuzzy expert systems shell), and COMAX (an autonomous fuzzy expert system for tactical communications networks. Fuzzy Expert Systems provides an invaluable reference resource for researchers and students in artificial intelligence (AI) and approximate reasoning (AR), as well as for other researchers looking for methods to apply similar tools in their own designs of intelligent systems.
Author: Rajendra Akerkar
Publisher: Jones & Bartlett Learning
ISBN: 0763776475
Category : Computers
Languages : en
Pages : 375
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Book Description
Knowledge Based Systems (KBS) are systems that use artificial intelligence techniques in the problem solving process. This text is designed to develop an appreciation of KBS and their architecture and to help users understand a broad variety of knowledge based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters are designed to be modular providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material being presented and to stimulate thought and discussion.
Author: Cornelius T. Leondes
Publisher: Elsevier
ISBN: 0080553192
Category : Computers
Languages : en
Pages : 437
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Book Description
This volume covers the integration of fuzzy logic and expert systems. A vital resource in the field, it includes techniques for applying fuzzy systems to neural networks for modeling and control, systematic design procedures for realizing fuzzy neural systems, techniques for the design of rule-based expert systems using the massively parallel processing capabilities of neural networks, the transformation of neural systems into rule-based expert systems, the characteristics and relative merits of integrating fuzzy sets, neural networks, genetic algorithms, and rough sets, and applications to system identification and control as well as nonparametric, nonlinear estimation. Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as computer scientists and engineers will appreciate this reference source to diverse application methodologies. - Fuzzy system techniques applied to neural networks for modeling and control - Systematic design procedures for realizing fuzzy neural systems - Techniques for the design of rule-based expert systems - Characteristics and relative merits of integrating fuzzy sets, neural networks, genetic algorithms, and rough sets - System identification and control - Nonparametric, nonlinear estimation Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as computer scientists and engineers will find this volume a unique and comprehensive reference to these diverse application methodologies
Author: Hung T. Nguyen
Publisher: Springer Science & Business Media
ISBN: 1461555051
Category : Mathematics
Languages : en
Pages : 532
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Book Description
The analysis and control of complex systems have been the main motivation for the emergence of fuzzy set theory since its inception. It is also a major research field where many applications, especially industrial ones, have made fuzzy logic famous. This unique handbook is devoted to an extensive, organized, and up-to-date presentation of fuzzy systems engineering methods. The book includes detailed material and extensive bibliographies, written by leading experts in the field, on topics such as: Use of fuzzy logic in various control systems. Fuzzy rule-based modeling and its universal approximation properties. Learning and tuning techniques for fuzzy models, using neural networks and genetic algorithms. Fuzzy control methods, including issues such as stability analysis and design techniques, as well as the relationship with traditional linear control. Fuzzy sets relation to the study of chaotic systems, and the fuzzy extension of set-valued approaches to systems modeling through the use of differential inclusions. Fuzzy Systems: Modeling and Control is part of The Handbooks of Fuzzy Sets Series. The series provides a complete picture of contemporary fuzzy set theory and its applications. This volume is a key reference for systems engineers and scientists seeking a guide to the vast amount of literature in fuzzy logic modeling and control.
