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Clustering and Neural Network Approaches for General NN-Simulator - Chandan Srivastava
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Chandan Srivastava:

Clustering and Neural Network Approaches for General NN-Simulator - neues Buch

ISBN: 9783845409429

ID: c1a9cb6ba0f84cea3c3a93745e06ea6c

K-means, K-mediods, Recurrent Backpropagation,and Artificial Neural Network Simulator This book is based on the basis that clustering and neural networks methods. The clustering algorithms (k-means, and k-medoids) are describe the analysis on noise data i.e. preclassification for robust model development. The better choice of cluster are forming by Euclidean statistical clustering algorithms, are able to preclassified data into significant groups. We assume that both methods are better predicted on different example in real analysis. The recurrent backpropagation is one of the best optimization techniques for minimizing the error and achieve the best optimal result. Since we have input unit, output unit, and eventually hidden unit; we could say that this is supervised optimization learning process. The optimization process to minimizing the error and get the activated network till that all weight of the network are going to reach equilibrium state). This process usually take more time because every output of network add-up with input again and train network (weight) to reach the equilibrium state (optimal solution).Reported results and graphical user interface (GUI) snapshot, showing algorithms are integrated well in software package (simulator). Bücher / Fremdsprachige Bücher / Englische Bücher 978-3-8454-0942-9, LAP Lambert Academic Publishing

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Clustering and Neural Network Approaches for General NN-Simulator - Chandan Srivastava
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)

Chandan Srivastava:

Clustering and Neural Network Approaches for General NN-Simulator - neues Buch

ISBN: 9783845409429

ID: b28504d08c819d307a53e07842ad617e

K-means, K-mediods, Recurrent Backpropagation,and Artificial Neural Network Simulator This book is based on the basis that clustering and neural networks methods. The clustering algorithms (k-means, and k-medoids) are describe the analysis on noise data i.e. preclassification for robust model development. The better choice of cluster are forming by Euclidean statistical clustering algorithms, are able to preclassified data into significant groups. We assume that both methods are better predicted on different example in real analysis.The recurrent backpropagation is one of the best optimization techniques for minimizing the error and achieve the best optimal result. Since we have input unit, output unit, and eventually hidden unit; we could say that this is supervised optimization learning process. The optimization process to minimizing the error and get the activated network till that all weight of the network are going to reach equilibrium state). This process usually take more time because every output of network add-up with input again and train network (weight) to reach the equilibrium state (optimal solution).Reported results and graphical user interface (GUI) snapshot, showing algorithms are integrated well in software package (simulator). Bücher / Fremdsprachige Bücher / Englische Bücher 978-3-8454-0942-9, LAP Lambert Academic Publishing

Neues Buch Buch.de
Nr. 29363707 Versandkosten:Bücher und alle Bestellungen die ein Buch enthalten sind versandkostenfrei, sonstige Bestellungen innerhalb Deutschland EUR 3,-, ab EUR 20,- kostenlos, Bürobedarf EUR 4,50, kostenlos ab EUR 45,-, Sofort lieferbar, DE. (EUR 0.00)
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(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Clustering and Neural Network Approaches for General NN-Simulator - Chandan Srivastava
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Chandan Srivastava:
Clustering and Neural Network Approaches for General NN-Simulator - neues Buch

ISBN: 9783845409429

ID: 210046376

This book is based on the basis that clustering and neural networks methods. The clustering algorithms (k-means, and k-medoids) are describe the analysis on noise data i.e. preclassification for robust model development. The better choice of cluster are forming by Euclidean statistical clustering algorithms, are able to preclassified data into significant groups. We assume that both methods are better predicted on different example in real analysis. The recurrent backpropagation is one of the best optimization techniques for minimizing the error and achieve the best optimal result. Since we have input unit, output unit, and eventually hidden unit; we could say that this is supervised optimization learning process. The optimization process to minimizing the error and get the activated network till that all weight of the network are going to reach equilibrium state). This process usually take more time because every output of network add-up with input again and train network (weight) to reach the equilibrium state (optimal solution).Reported results and graphical user interface (GUI) snapshot, showing algorithms are integrated well in software package (simulator). K-means, K-mediods, Recurrent Backpropagation,and Artificial Neural Network Simulator Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, LAP Lambert Academic Publishing

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(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Clustering and Neural Network Approaches for General NN-Simulator - Chandan Srivastava
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Chandan Srivastava:
Clustering and Neural Network Approaches for General NN-Simulator - neues Buch

ISBN: 9783845409429

ID: b28504d08c819d307a53e07842ad617e

K-means, K-mediods, Recurrent Backpropagation,and Artificial Neural Network Simulator This book is based on the basis that clustering and neural networks methods. The clustering algorithms (k-means, and k-medoids) are describe the analysis on noise data i.e. preclassification for robust model development. The better choice of cluster are forming by Euclidean statistical clustering algorithms, are able to preclassified data into significant groups. We assume that both methods are better predicted on different example in real analysis.The recurrent backpropagation is one of the best optimization techniques for minimizing the error and achieve the best optimal result. Since we have input unit, output unit, and eventually hidden unit; we could say that this is supervised optimization learning process. The optimization process to minimizing the error and get the activated network till that all weight of the network are going to reach equilibrium state). This process usually take more time because every output of network add-up with input again and train network (weight) to reach the equilibrium state (optimal solution).Reported results and graphical user interface (GUI) snapshot, showing algorithms are integrated well in software package (simulator). Bücher / Fremdsprachige Bücher / Englische Bücher 978-3-8454-0942-9, LAP Lambert Acad. Publ.

Neues Buch Buch.de
Nr. 29363707 Versandkosten:Bücher und alle Bestellungen die ein Buch enthalten sind versandkostenfrei, sonstige Bestellungen innerhalb Deutschland EUR 3,-, ab EUR 20,- kostenlos, Bürobedarf EUR 4,50, kostenlos ab EUR 45,-, Sofort lieferbar, DE. (EUR 0.00)
Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Clustering and Neural Network Approaches for General NN-Simulator - Chandan Srivastava
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Chandan Srivastava:
Clustering and Neural Network Approaches for General NN-Simulator - neues Buch

ISBN: 9783845409429

ID: 210046376

This book is based on the basis that clustering and neural networks methods. The clustering algorithms (k-means, and k-medoids) are describe the analysis on noise data i.e. preclassification for robust model development. The better choice of cluster are forming by Euclidean statistical clustering algorithms, are able to preclassified data into significant groups. We assume that both methods are better predicted on different example in real analysis.The recurrent backpropagation is one of the best optimization techniques for minimizing the error and achieve the best optimal result. Since we have input unit, output unit, and eventually hidden unit; we could say that this is supervised optimization learning process. The optimization process to minimizing the error and get the activated network till that all weight of the network are going to reach equilibrium state). This process usually take more time because every output of network add-up with input again and train network (weight) to reach the equilibrium state (optimal solution).Reported results and graphical user interface (GUI) snapshot, showing algorithms are integrated well in software package (simulator). K-means, K-mediods, Recurrent Backpropagation,and Artificial Neural Network Simulator Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, LAP Lambert Acad. Publ.

Neues Buch Thalia.de
No. 29363707 Versandkosten:, Versandfertig in 2 - 3 Tagen, DE (EUR 0.00)
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Clustering and Neural Network Approaches for General NN-Simulator
Autor:

Srivastava, Chandan

Titel:

Clustering and Neural Network Approaches for General NN-Simulator

ISBN-Nummer:

3845409428

Detailangaben zum Buch - Clustering and Neural Network Approaches for General NN-Simulator


EAN (ISBN-13): 9783845409429
ISBN (ISBN-10): 3845409428
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2011
Herausgeber: LAP Lambert Acad. Publ.

Buch in der Datenbank seit 20.11.2008 21:56:41
Buch zuletzt gefunden am 11.04.2016 12:01:45
ISBN/EAN: 3845409428

ISBN - alternative Schreibweisen:
3-8454-0942-8, 978-3-8454-0942-9

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