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Soft computing based system modeling & control - Softcover

 
9783659823664: Soft computing based system modeling & control

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Several clustering algorithms have been explained in the book including kernel based clustering algorithm. A kernel based clustering incorporates a kernel metric in place of the Euclidean distance used in the objective function. The kernel induced metric maps the data points to a high dimensional feature space, in which the data is more clearly separable, thereby increasing the accuracy of the proposed clustering technique. A fuzzy controller can also be designed using the clustering based approach. Clustering-based rule extraction methods help avoid combinatorial explosion of rules with increasing dimension of the input space. Also, because clustering step provides good initial rule parameter values, the subsequent rule parameter optimization process usually converges quickly and to a good solution.

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Dr Meena Tushir has been working with the Department of Electrical & Electronics Engineering, MSIT, New Delhi, India since 2003 where she is currently holds the position of Associate Professor. Her current research interests include neural networks, fuzzy logic, modelling, identification, and control of non-linear systems.

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ISBN 10: 365982366X ISBN 13: 9783659823664
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Several clustering algorithms have been explained in the book including kernel based clustering algorithm. A kernel based clustering incorporates a kernel metric in place of the Euclidean distance used in the objective function. The kernel induced metric maps the data points to a high dimensional feature space, in which the data is more clearly separable, thereby increasing the accuracy of the proposed clustering technique. A fuzzy controller can also be designed using the clustering based approach. Clustering-based rule extraction methods help avoid combinatorial explosion of rules with increasing dimension of the input space. Also, because clustering step provides good initial rule parameter values, the subsequent rule parameter optimization process usually converges quickly and to a good solution. 96 pp. Englisch. Seller Inventory # 9783659823664

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Published by LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365982366X ISBN 13: 9783659823664
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Several clustering algorithms have been explained in the book including kernel based clustering algorithm. A kernel based clustering incorporates a kernel metric in place of the Euclidean distance used in the objective function. The kernel induced metric maps the data points to a high dimensional feature space, in which the data is more clearly separable, thereby increasing the accuracy of the proposed clustering technique. A fuzzy controller can also be designed using the clustering based approach. Clustering-based rule extraction methods help avoid combinatorial explosion of rules with increasing dimension of the input space. Also, because clustering step provides good initial rule parameter values, the subsequent rule parameter optimization process usually converges quickly and to a good solution. Seller Inventory # 9783659823664

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Published by LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365982366X ISBN 13: 9783659823664
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tushir MeenaDr Meena Tushir has been working with the Department of Electrical & Electronics Engineering, MSIT, New Delhi, India since 2003 where she is currently holds the position of Associate Professor. Her current research intere. Seller Inventory # 158605834

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Paperback. Condition: Brand New. 96 pages. 8.66x5.91x0.22 inches. In Stock. Seller Inventory # 365982366X

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Several clustering algorithms have been explained in the book including kernel based clustering algorithm. A kernel based clustering incorporates a kernel metric in place of the Euclidean distance used in the objective function. The kernel induced metric maps the data points to a high dimensional feature space, in which the data is more clearly separable, thereby increasing the accuracy of the proposed clustering technique. A fuzzy controller can also be designed using the clustering based approach. Clustering-based rule extraction methods help avoid combinatorial explosion of rules with increasing dimension of the input space. Also, because clustering step provides good initial rule parameter values, the subsequent rule parameter optimization process usually converges quickly and to a good solution.Books on Demand GmbH, Überseering 33, 22297 Hamburg 96 pp. Englisch. Seller Inventory # 9783659823664

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