Soft Computing Based System by Tushir Meena (7 results)
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 96 pages. 8.66x5.91x0.22 inches. In Stock.
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- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Soft computing based system modeling & control | Meena Tushir | Taschenbuch | 96 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659823664 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
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paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Language: English
Published by LAP LAMBERT Academic Publishing Jan 2016, 2016
- Softcover
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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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.
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- Softcover
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Seller: moluna, Greven, Germanymoluna
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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 Profess…or. Her current research intere.
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Language: English
Published by LAP LAMBERT Academic Publishing Jan 2016, 2016
- Softcover
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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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 ker…nel 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch.
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- Softcover
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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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 kern…el 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.
