Neural Fuzzy Control Systems With Structure And Parameter Learning
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| Author | : Chin-teng Lin |
| Publisher | : World Scientific Publishing Company |
| Total Pages | : 152 |
| Release | : 1994-02-08 |
| Genre | : Technology & Engineering |
| ISBN | : 9813104708 |
A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.
| Author | : Ching Tai Lin |
| Publisher | : |
| Total Pages | : 127 |
| Release | : 1994 |
| Genre | : |
| ISBN | : 9789814354240 |
| Author | : C. T. Lin |
| Publisher | : World Scientific |
| Total Pages | : 150 |
| Release | : 1994 |
| Genre | : Computers |
| ISBN | : 9789810216139 |
A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.
| Author | : Ching Tai Lin |
| Publisher | : Prentice Hall |
| Total Pages | : 824 |
| Release | : 1996 |
| Genre | : Computers |
| ISBN | : |
Neural Fuzzy Systems provides a comprehensive, up-to-date introduction to the basic theories of fuzzy systems and neural networks, as well as an exploration of how these two fields can be integrated to create Neural-Fuzzy Systems. It includes Matlab software, with a Neural Network Toolkit, and a Fuzzy System Toolkit.
| Author | : Abraham Kandel |
| Publisher | : CRC Press |
| Total Pages | : 664 |
| Release | : 1993-09-27 |
| Genre | : Computers |
| ISBN | : 9780849344961 |
Fuzzy Control Systems explores one of the most active areas of research involving fuzzy set theory. The contributors address basic issues concerning the analysis, design, and application of fuzzy control systems. Divided into three parts, the book first devotes itself to the general theory of fuzzy control systems. The second part deals with a variety of methodologies and algorithms used in the analysis and design of fuzzy controllers. The various paradigms include fuzzy reasoning models, fuzzy neural networks, fuzzy expert systems, and genetic algorithms. The final part considers current applications of fuzzy control systems. This book should be required reading for researchers, practitioners, and students interested in fuzzy control systems, artificial intelligence, and fuzzy sets and systems.
| Author | : Leszek Rutkowski |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 286 |
| Release | : 2004-05-19 |
| Genre | : Computers |
| ISBN | : 1402080425 |
Flexible Neuro-Fuzzy Systems is the first professional literature about the new class of powerful, flexible fuzzy systems. The author incorporates various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data. Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features: -Provides a framework for unification, construction and development of neuro-fuzzy systems; -Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation, -Covers not only advanced topics but also fundamentals of fuzzy sets, -Includes problems and exercises following each chapter, -Illustrates the results on a wide variety of simulations, -Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering.
| Author | : Jelena Godjevac |
| Publisher | : EPFL Press |
| Total Pages | : 172 |
| Release | : 1997-01-01 |
| Genre | : Fuzzy logic |
| ISBN | : 9782880743550 |
| Author | : Ching Tai Lin |
| Publisher | : |
| Total Pages | : 797 |
| Release | : 1996 |
| Genre | : Fuzzy systems |
| ISBN | : 9789867910547 |
| Author | : Junhong Nie |
| Publisher | : Prentice Hall PTR |
| Total Pages | : 262 |
| Release | : 1995 |
| Genre | : Computers |
| ISBN | : |
Illustrating how fuzzy logic and neural networks can be integrated into a model reference control context for real-time control of multivariable systems, this book provides an architecture which accommodates several popular learning/reasoning paradigms.
| Author | : H. B. Verbruggen |
| Publisher | : World Scientific |
| Total Pages | : 344 |
| Release | : 1999 |
| Genre | : Technology & Engineering |
| ISBN | : 9789810238254 |
Fuzzy logic control has become an important methodology in control engineering. This volume deals with applications of fuzzy logic control in various domains. The contributions are divided into three parts. The first part consists of two state-of-the-art tutorials on fuzzy control and fuzzy modeling. Surveys of advanced methodologies are included in the second part. These surveys address fuzzy decision making and control, fault detection, isolation and diagnosis, complexity reduction in fuzzy systems and neuro-fuzzy methods. The third part contains application-oriented contributions from various fields, such as process industry, cement and ceramics, vehicle control and traffic management, electromechanical and production systems, avionics, biotechnology and medical applications. The book is intended for researchers both from the academic world and from industry.
