Items related to Design Fast Feed Forward Neural Networks To Solve SBVP
Synopsis
The aim of this book is to design fast feed forward neural networks to present a method to solve singular boundary value problems for ordinary differential equations.The suggested networks use the principle of Back propagation with different training algorithms such as Levenberg–Marquardt, quasi-Newton and Bayesian regularization, update procedure then speeding suggested networks by modification these training algorithms.The Main objective of this book is to find the best training algorithm to solve singular boundary value problems. Other aim of this book, is to study the mathematical models for the equations describe the temperature variation of a spherical gas cloud under the mutual attraction of its molecules and subject to the laws of classical thermodynamics. These equations are one of the basic equations in the theory of stellar structure and have been the focus of many studies, so use the suggested networks to solve this equations. Finally, we illustrate the suggested network by solving a variety of model problems and present comparisons with solutions obtained using other different methods to show speed, accuracy and effectiveness of using the networks technique.
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About the Author
Ashraf Adnan Thirthar al.qaisy I was born 14/09/1988 earned a bachelor's degree In mathematics from the University of Anbar, the year 2009 AD and then earned a master's degree In mathematics from the University of Baghdad in 2014 AD .I have a number of published papers in international journals and I participate in an international conference.
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Design Fast Feed Forward Neural Networks To Solve SBVP
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LAP LAMBERT Academic Publishing Mär 2014, 2014
ISBN 10: 3659168440
ISBN 13: 9783659168444
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The aim of this book is to design fast feed forward neural networks to present a method to solve singular boundary value problems for ordinary differential equations.The suggested networks use the principle of Back propagation with different training algorithms such as Levenberg-Marquardt, quasi-Newton and Bayesian regularization, update procedure then speeding suggested networks by modification these training algorithms.The Main objective of this book is to find the best training algorithm to solve singular boundary value problems. Other aim of this book, is to study the mathematical models for the equations describe the temperature variation of a spherical gas cloud under the mutual attraction of its molecules and subject to the laws of classical thermodynamics. These equations are one of the basic equations in the theory of stellar structure and have been the focus of many studies, so use the suggested networks to solve this equations. Finally, we illustrate the suggested network by solving a variety of model problems and present comparisons with solutions obtained using other different methods to show speed, accuracy and effectiveness of using the networks technique. 212 pp. Englisch. Seller Inventory # 9783659168444
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Design Fast Feed Forward Neural Networks To Solve SBVP
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ISBN 13: 9783659168444
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Thirthar Hussein Ashraf AdnanAshraf Adnan Thirthar al.qaisy I was born 14/09/1988 earned a bachelor s degree In mathematics from the University of Anbar, the year 2009 AD and then earned a master s degree In mathematics from the Univ. Seller Inventory # 5136561
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Design Fast Feed Forward Neural Networks To Solve SBVP
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LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659168440
ISBN 13: 9783659168444
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Taschenbuch. Condition: Neu. Design Fast Feed Forward Neural Networks To Solve SBVP | Ashraf Adnan Thirthar Hussein (u. a.) | Taschenbuch | 212 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659168444 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 105335743
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Design Fast Feed Forward Neural Networks To Solve SBVP
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LAP LAMBERT Academic Publishing Mär 2014, 2014
ISBN 10: 3659168440
ISBN 13: 9783659168444
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The aim of this book is to design fast feed forward neural networks to present a method to solve singular boundary value problems for ordinary differential equations.The suggested networks use the principle of Back propagation with different training algorithms such as Levenberg-Marquardt, quasi-Newton and Bayesian regularization, update procedure then speeding suggested networks by modification these training algorithms.The Main objective of this book is to find the best training algorithm to solve singular boundary value problems. Other aim of this book, is to study the mathematical models for the equations describe the temperature variation of a spherical gas cloud under the mutual attraction of its molecules and subject to the laws of classical thermodynamics. These equations are one of the basic equations in the theory of stellar structure and have been the focus of many studies, so use the suggested networks to solve this equations. Finally, we illustrate the suggested network by solving a variety of model problems and present comparisons with solutions obtained using other different methods to show speed, accuracy and effectiveness of using the networks technique.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 212 pp. Englisch. Seller Inventory # 9783659168444
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Design Fast Feed Forward Neural Networks To Solve SBVP
Published by
LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659168440
ISBN 13: 9783659168444
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Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The aim of this book is to design fast feed forward neural networks to present a method to solve singular boundary value problems for ordinary differential equations.The suggested networks use the principle of Back propagation with different training algorithms such as Levenberg-Marquardt, quasi-Newton and Bayesian regularization, update procedure then speeding suggested networks by modification these training algorithms.The Main objective of this book is to find the best training algorithm to solve singular boundary value problems. Other aim of this book, is to study the mathematical models for the equations describe the temperature variation of a spherical gas cloud under the mutual attraction of its molecules and subject to the laws of classical thermodynamics. These equations are one of the basic equations in the theory of stellar structure and have been the focus of many studies, so use the suggested networks to solve this equations. Finally, we illustrate the suggested network by solving a variety of model problems and present comparisons with solutions obtained using other different methods to show speed, accuracy and effectiveness of using the networks technique. Seller Inventory # 9783659168444