Fuzzy Networks for Complex Systems

Fuzzy Networks for Complex Systems

Author: Alexander Gegov

Publisher: Springer

ISBN: 9783642156007

Category: Technology & Engineering

Page: 290

View: 548

This book introduces the novel concept of a fuzzy network whose nodes are rule bases and the connections between the nodes are the interactions between the rule bases in the form of outputs fed as inputs. The concept is presented as a systematic study for improving the feasibility and transparency of fuzzy models by means of modular rule bases whereby the model accuracy and efficiency can be optimised in a flexible way. The study uses an effective approach for fuzzy rule based modelling of complex systems that are characterised by attributes such as nonlinearity, uncertainty, dimensionality and structure.The approach is illustrated by formal models for fuzzy networks, basic and advanced operations on network nodes, properties of operations, feedforward and feedback fuzzy networks as well as evaluation of fuzzy networks. The results are demonstrated by numerous examples, two case studies and software programmes within the Matlab environment that implement some of the theoretical methods from the book. The book shows the novel concept of a fuzzy network with networked rule bases as a bridge between the existing concepts of a standard fuzzy system with a single rule base and a hierarchical fuzzy system with multiple rule bases.

Fuzzy Networks for Complex Systems
Language: en
Pages: 290
Authors: Alexander Gegov
Categories: Technology & Engineering
Type: BOOK - Published: 2010-09-30 - Publisher: Springer

This book introduces the novel concept of a fuzzy network whose nodes are rule bases and the connections between the nodes are the interactions between the rule bases in the form of outputs fed as inputs. The concept is presented as a systematic study for improving the feasibility and transparency
Fuzzy Networks for Complex Systems
Language: en
Pages: 290
Authors: Alexander Gegov
Categories: Mathematics
Type: BOOK - Published: 2010-10-04 - Publisher: Springer Science & Business Media

This book introduces the novel concept of a fuzzy network whose nodes are rule bases and the connections between the nodes are the interactions between the rule bases in the form of outputs fed as inputs. The concept is presented as a systematic study for improving the feasibility and transparency
Fuzzy Logic for the Applications to Complex Systems
Language: en
Pages: 592
Authors: Weiling Chiang, Jonathan Lee
Categories: Mathematics
Type: BOOK - Published: 1995-11-16 - Publisher: World Scientific

This volume presents an interesting mix of topics on complex systems such as information systems, engineering systems, fuzzy neural systems, image processing, robotics, fuzzy control, genetic algorithms, and fuzzy decision making. The contributions come from 12 countries, and provide a clear picture of fuzzy logic applications worldwide. Contents:LIFE Project in
Type-2 Fuzzy Logic in Intelligent Control Applications
Language: en
Pages: 190
Authors: Oscar Castillo
Categories: Computers
Type: BOOK - Published: 2011-11-08 - Publisher: Springer

We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts,
Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms
Language: en
Pages: 368
Authors: Lakhmi C. Jain, N.M. Martin
Categories: Computers
Type: BOOK - Published: 2020-01-29 - Publisher: CRC Press

Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist