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Neural Networks and Fuzzy Systems : Theory and Applications 🔍
Shigeo Abe (auth.) Springer US : Imprint : Springer, 1, 1997
英语 [en] · PDF · 10.9MB · 1997 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save
描述
__Neural Networks and Fuzzy Systems: Theory and Applications__ discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems. The book includes performance comparison of neural networks and fuzzy systems using data gathered from real systems. Topics covered include the Hopfield network for combinatorial optimization problems, multilayered neural networks for pattern classification and function approximation, fuzzy systems that have the same functions as multilayered networks, and composite systems that have been successfully applied to real world problems. The author also includes representative neural network models such as the Kohonen network and radial basis function network. New fuzzy systems with learning capabilities are also covered. The advantages and disadvantages of neural networks and fuzzy systems are examined. The performance of these two systems in license plate recognition, a water purification plant, blood cell classification, and other real world problems is compared.
备用文件名
lgrsnf/A:\compressed\10.1007%2F978-1-4615-6253-5.pdf
备用文件名
nexusstc/Neural Networks and Fuzzy Systems/f33668bda3bf0928fcbd2c5dbbf00ef1.pdf
备用文件名
scihub/10.1007/978-1-4615-6253-5.pdf
备用文件名
zlib/Computers/Computer Science/Shigeo Abe (auth.)/Neural Networks and Fuzzy Systems: Theory and Applications_2098280.pdf
备选作者
by Shigeo Abe
备用出版商
Springer Science+Business Media
备用出版商
Kluwer Academic
备用版本
United States, United States of America
备用版本
Springer Nature, New York, NY, 2012
备用版本
Boston, MA, Massachusetts, 1997
备用版本
New York, 1997
备用版本
Oct 30, 2012
备用版本
1, 2013
元数据中的注释
sm43274785
元数据中的注释
{"edition":"1","isbns":["1461378699","1461562538","9781461378693","9781461562535"],"last_page":258,"publisher":"Springer US"}
备用描述
<em>neural Networks And Fuzzy Systems: Theory And Applications</em> Discusses Theories That Have Proven Useful In Applying Neural Networks And Fuzzy Systems To Real World Problems. The Book Includes Performance Comparison Of Neural Networks And Fuzzy Systems Using Data Gathered From Real Systems. Topics Covered Include The Hopfield Network For Combinatorial Optimization Problems, Multilayered Neural Networks For Pattern Classification And Function Approximation, Fuzzy Systems That Have The Same Functions As Multilayered Networks, And Composite Systems That Have Been Successfully Applied To Real World Problems. The Author Also Includes Representative Neural Network Models Such As The Kohonen Network And Radial Basis Function Network. New Fuzzy Systems With Learning Capabilities Are Also Covered. <br> The Advantages And Disadvantages Of Neural Networks And Fuzzy Systems Are Examined. The Performance Of These Two Systems In License Plate Recognition, A Water Purification Plant, Blood Cell Classification, And Other Real World Problems Is Compared.
备用描述
Front Matter....Pages i-xvi
Overview of Neural Networks....Pages 1-5
The Hopfield Network....Pages 7-43
Multilayered Networks....Pages 45-91
Other Neural Networks....Pages 93-125
Overview of Fuzzy Systems....Pages 127-149
Fuzzy Rule Extraction for Pattern Classification from Numerical Data....Pages 151-197
Fuzzy Rule Extraction for Function Approximation from Numerical Data....Pages 199-208
Composite Systems....Pages 209-224
Back Matter....Pages 225-258
备用描述
Keine Beschreibung vorhanden.
Erscheinungsdatum: 30.10.2012
开源日期
2013-08-01
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