» » Soft Computing: Integrating Evolutionary, Neural, and Fuzzy Systems

epub Soft Computing: Integrating Evolutionary, Neural, and Fuzzy Systems download

by Marco Tomassini,J. Janßen,Andrea Tettamanzi

  • ISBN: 3540422048
  • Author: Marco Tomassini,J. Janßen,Andrea Tettamanzi
  • ePub ver: 1778 kb
  • Fb2 ver: 1778 kb
  • Rating: 4.1 of 5
  • Language: English
  • Pages: 327
  • Publisher: Springer; 2001 edition (October 16, 2001)
  • Formats: azw mbr docx doc
  • Category: IT
  • Subcategory: Computer Science
epub Soft Computing: Integrating Evolutionary, Neural, and Fuzzy Systems download

Andrea Tettamanzi (Author), Marco Tomassini (Author), J. Janßen (Cover Design) & 0 more.

Andrea Tettamanzi (Author), Marco Tomassini (Author), J.

Soft computing technologies offer adaptability as a characteristic feature . 62 Fuzzy Neural Networks. 203. 63 Cooperative Neurofuzzy Systems. Andrea Tettamanzi, Marco Tomassini. Mitwirkende Personen.

Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing.

Authors: Tettamanzi, Andrea G. Tomassini, Marco. Andrea G. B. Tettamanzi. eBook 59,49 €. price for Russian Federation (gross).

Goodreads helps you keep track of books you want to read

Goodreads helps you keep track of books you want to read.

This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. Your Shopping Basket. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. Andrea Tettamanzi Marco Tomassini J. Jansen.

Try checking your spelling or use more general terms.

The book is primarily aimed at undergraduate students and practitioners in the field. The book is organized in a modular form which enable readers to select their own pathway through the chapters. The academic content is well supported by informative practical examples and case studies.

This Chapter deals with neuro-fuzzy systems, i. those soft computing methods that combine in various ways neural networks and fuzzy concepts

Chapter · January 2001 with 5 Reads. Cite this publication. This Chapter deals with neuro-fuzzy systems, i. those soft computing methods that combine in various ways neural networks and fuzzy concepts. Each methodology has its particular strengths and weaknesses that make it more or less suitable in a given context. For example, fuzzy systems can reason with imprecise information and have good explanatory power.

Fuzzy Systems; Evolutionary Design of Artificial Neural Networks .

Fuzzy Systems; Evolutionary Design of Artificial Neural Networks; Evolutionary Design of Fuzzy Systems; Neuro-fuzzy Systems; Fuzzy Evolutionary Algorithms; Natural Parallel (Soft) Computing; Epilogue. Among the topics addressed are fuzzy systems, soft computing, neural networks, pattern recognition, image processing, evolutionary computation, and data mining. 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.

Andrea Tettamanzi, Marco Tomassini. This paper presents an approach to the joint optimization of neural network structure and weights which can take advantage of backpropagation as a specialized decoder. The approach has been applie. More).

Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically.This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

Related to Soft Computing: Integrating Evolutionary, Neural, and Fuzzy Systems: