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eBook Genetic Algorithms and Soft Computing (Studies in Fuzziness and Soft Computing) epub

by Francisco Herrera,Jose Luis Verdegay

eBook Genetic Algorithms and Soft Computing (Studies in Fuzziness and Soft Computing) epub
  • ISBN: 379080956X
  • Author: Francisco Herrera,Jose Luis Verdegay
  • Genre: Techno
  • Subcategory: Computer Science
  • Language: English
  • Publisher: Physica; 1 edition (October 1, 1996)
  • Pages: 709 pages
  • ePUB size: 1959 kb
  • FB2 size 1326 kb
  • Formats docx lrf txt mobi


Soft Computing is concerned with modes of computing in which precision is treated for . Studies in Fuzziness and Soft Computing.

Soft Computing is concerned with modes of computing in which precision is treated for tractability, robustness and ease of implementation, and it contains Fuzzy Sets and Genetic Algorithms among its components. Each of them have different advantages to deal with nonlinearity or explicit knowledge.

The algorithm has been tested with 15 subjects of varying ages on a flat and plain surface.

The learning methods, clustering of input space, use of different fuzzy implications in inference process and other related topics are shown. In such processes, the soft computing techniques : Fuzzy time series and Artificial. neural network be preferred as these use the relation of dependency and knowledge by learning process of set of training data. The algorithm has been tested with 15 subjects of varying ages on a flat and plain surface.

Start by marking Genetic Algorithms And Soft Computing as Want to Read .

Start by marking Genetic Algorithms And Soft Computing as Want to Read: Want to Read savin. ant to Read. Soft Computing is concerned with modes of computing in which precision is treated for tractability, robustness and ease of implementation, and it contains Fuzzy Sets and Genetic Algorithms among its components. This book will be revealing for all those interested in new developments and practical applications in the interface between Soft Computing and Genetic Algorithms.

Studies in Fuzziness and Soft Computing). Humberto Bustince, Francisco Herrera, Javier Montero. The book contains 34 chapters divided into two parts. The first part is divided into two sections

of Computer Science and . University of Granada, Spain We will introduce Soft Computing techniques: Fuzzy Logic, Genetic Algorithms, and we will present the use of Soft Computing tecniques in Data Mining 2. 3 Material of this course at: 3.

oceedings{, title {Genetic Algorithms and Soft Computing}, author . Francisco Herrera, José L. Verdegay. Contents: Foundations. Fuzzy Logic Based Techniques in Genetic Algorithms.

oceedings{, title {Genetic Algorithms and Soft Computing}, author {Francisco Herrera and Jos{'e} L. Verdegay}, year {1996} }. Learning in Fuzzy Controllers. Optimization of Fuzzy Controllers. Fuzzy Classifier Systems. Genetic Algorithms in Fuzzy Contexts.

José Luis VerdegayProfessor of Computer Science and Artificial Intelligence, University of GranadaVerified . Journal of Multiple-Valued Logic and Soft Computing 17 (2-3), 255-287, 2011. F Herrera, M Lozano, JL Verdegay.

Journal of Multiple-Valued Logic and Soft Computing 17 (2-3), 255-287, 2011.

Series: Studies in Fuzziness and Soft Computing (Book 104). I've enjoyed studying the topics in this book. Paperback: 290 pages. ISBN-13: 978-3642880964.

Francisco HerreraProfessor Computer Science and AI, Granada Univ. Genetic Algorithms and Soft Computing. F Herrera, JL Verdegay. Physica-Verlag, 1996. Soft Computing Artificial Intelligence Metaheuristics Fuzzy Mathematical Programing Computational Intelligence. Articles Cited by Co-authors. Tackling real-coded genetic algorithms: Operators and tools for behavioural analysis. A model of consensus in group decision making under linguistic assessments. F Herrera, E Herrera-Viedma, JL Verdegay.

Soft Computing is concerned with modes of computing in which precision is treated for tractability, robustness and ease of implementation, and it contains Fuzzy Sets and Genetic Algorithms among its components. Each of them have different advantages to deal with nonlinearity or explicit knowledge expression, but learning capability, as well as global and local search approaches provided by Genetic Algorithms are remarkable. This book will be revealing for all those interested in new developments and practical applications in the interface between Soft Computing and Genetic Algorithms.
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