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Sinopsis
Artificial neural network is designed with the goal of building intelligent machines to solve complex perceptual problems, such as pattern classification, by mimicking the networks of real neurons in the human brain. To achieve better performance over a single neural network, ensembles construction with several neural networks has become a nutritious filed of research. This book presents the basics of ensemble construction and discusses several existing ensemble methods. A large number of benchmark problems from different application domains were considered for evaluating the methods. After the discussion of the existing methods three new different techniques of ensemble constructions are explained in three different chapters. Last two chapters of this book are to discuss the new techniques on a common ground and draw the conclusions of this work together with the outline of future directions of research opened by this work.
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Acerca de los autores
M. A. H. Akhand received doctoral degree in System Design Engineering from Univ. of Fukui, Japan. He is an Assist. Prof., Dept. of CSE, Khulna Univ. of Engineering & Technology, Bangladesh. K. Murase received PhD in Biomedical Engineering from Iowa State Univ. He is a Prof. of Human and Artificial Intelligence Systems Dept., Univ. of Fukui.
M. A. H. Akhand received doctoral degree in System Design Engineering from Univ. of Fukui, Japan. He is an Assist. Prof., Dept. of CSE, Khulna Univ. of Engineering & Technology, Bangladesh. K. Murase received PhD in Biomedical Engineering from Iowa State Univ. He is a Prof. of Human and Artificial Intelligence Systems Dept., Univ. of Fukui.
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Neural Networks Ensembles
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LAP LAMBERT Academic Publishing Aug 2010, 2010
ISBN 10: 3838391373
ISBN 13: 9783838391373
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Artificial neural network is designed with the goal of building intelligent machines to solve complex perceptual problems, such as pattern classification, by mimicking the networks of real neurons in the human brain. To achieve better performance over a single neural network, ensembles construction with several neural networks has become a nutritious filed of research. This book presents the basics of ensemble construction and discusses several existing ensemble methods. A large number of benchmark problems from different application domains were considered for evaluating the methods. After the discussion of the existing methods three new different techniques of ensemble constructions are explained in three different chapters. Last two chapters of this book are to discuss the new techniques on a common ground and draw the conclusions of this work together with the outline of future directions of research opened by this work. 152 pp. Englisch. Nº de ref. del artículo: 9783838391373
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Neural Networks Ensembles : Existing Methods and New Techniques
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838391373
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial neural network is designed with the goal of building intelligent machines to solve complex perceptual problems, such as pattern classification, by mimicking the networks of real neurons in the human brain. To achieve better performance over a single neural network, ensembles construction with several neural networks has become a nutritious filed of research. This book presents the basics of ensemble construction and discusses several existing ensemble methods. A large number of benchmark problems from different application domains were considered for evaluating the methods. After the discussion of the existing methods three new different techniques of ensemble constructions are explained in three different chapters. Last two chapters of this book are to discuss the new techniques on a common ground and draw the conclusions of this work together with the outline of future directions of research opened by this work. Nº de ref. del artículo: 9783838391373
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Neural Networks Ensembles
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Akhand M. A. H.M. A. H. Akhand received doctoral degree in System Design Engineering from Univ. of Fukui, Japan. He is an Assist. Prof., Dept. of CSE, Khulna Univ. of Engineering & Technology, Bangladesh. K. Murase received PhD in. Nº de ref. del artículo: 5419374
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Neural Networks Ensembles
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ISBN 13: 9783838391373
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Artificial neural network is designed with the goal of building intelligent machines to solve complex perceptual problems, such as pattern classification, by mimicking the networks of real neurons in the human brain. To achieve better performance over a single neural network, ensembles construction with several neural networks has become a nutritious filed of research. This book presents the basics of ensemble construction and discusses several existing ensemble methods. A large number of benchmark problems from different application domains were considered for evaluating the methods. After the discussion of the existing methods three new different techniques of ensemble constructions are explained in three different chapters. Last two chapters of this book are to discuss the new techniques on a common ground and draw the conclusions of this work together with the outline of future directions of research opened by this work.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch. Nº de ref. del artículo: 9783838391373
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Neural Networks Ensembles | Existing Methods and New Techniques
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Taschenbuch. Condición: Neu. Neural Networks Ensembles | Existing Methods and New Techniques | M. A. H. Akhand (u. a.) | Taschenbuch | 152 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838391373 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 107421910
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Neural Networks Ensembles: Existing Methods and New Techniques
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