- 416 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Fuzzy Logic and Expert Systems Applications
About this book
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
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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 Fuzzy Logic and Expert Systems Applications by Cornelius T. Leondes 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.
Information
Wavelets in Identification
A. Juditsky Institut de Recherche en Informatique et Systemes Aleatoires (IRISA), Campus Universitaire de Beaulieu, 35042 Rennes Cedex, France
P.-Y. Glorennec Institut de Recherche en Informatique et Systemes Aleatoires (IRISA), Campus Universitaire de Beaulieu, 35042 Rennes Cedex, France
Q. Zhang Institut de Recherche en Informatique et Systemes Aleatoires (IRISA), Campus Universitaire de Beaulieu, 35042 Rennes Cedex, France
A. Benveniste Institut de Recherche en Informatique et Systemes Aleatoires (IRISA), Campus Universitaire de Beaulieu, 35042 Rennes Cedex, France
B. Delyon Institut de Recherche en Informatique et Systemes Aleatoires (IRISA), Campus Universitaire de Beaulieu, 35042 Rennes Cedex, France
I INTRODUCTION, MOTIVATIONS, BASIC PROBLEMS
In his inspiring tutorial [1], Ljung quoted the following:
An engineer, who is faced with [characterizing, or predicting, the behavior of his or her plant based on recorded data] has the following perspective:
• How can I best use the information in the observed data to calculate a model of the system’s properties?
• How can I know if the model is any good, and how can I trust it for simulation and design purposes?
• How shall I manipulate the input signals to obtain as much information as possible about the system?
• What kind of software support is available for doing the tasks?
Later on in the same article, Ljung discusses the question of model nature and structure. By model nature, we have in mind the following classification:
• physical mo...
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright page
- Contributors
- Preface
- Fuzzy Neural Networks Techniques and Their Applications
- Implementation of Fuzzy Systems
- Neural Networks and Rule-Based Systems
- Construction of Rule-Based Intelligent Systems
- Expert Systems in Soft Computing Paradigm
- Mean-Value-Based Functional Reasoning Techniques in the Development of Fuzzy Neural Network Control Systems
- Fuzzy Neural Network Systems in Model Reference Control Systems
- Wavelets in Identification
- Index