Fast Feed Forward Neural Networks to Solve Boundary Value Problems | Fast Feed Forward Neural Networks

Muna Ali (u. a.)

ISBN 10: 3659313033 / ISBN 13: 9783659313035

Published by LAP Lambert Academic Publishing, 2012

About this Item

Fast Feed Forward Neural Networks to Solve Boundary Value Problems | Fast Feed Forward Neural Networks | Muna Ali (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659313035 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106088302

Bibliographic Details

• Title: Fast Feed Forward Neural Networks to Solve Boundary Value Problems | Fast Feed Forward Neural Networks
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3659313033
• ISBN 13: 9783659313035
• Binding: Taschenbuch
• Condition: Neu
• Seller catalogs:
  • Bücher

About this title

Synopsis

The aim of this book is to design fast feed forward neural networks to present a method to solve two point boundary value problems for ordinary differential equations, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speedup the solution times, reduce solver failures, and increase possibility of obtaining the globally optimal solution. We training suggested network by Levenberg – Marquardt, BFGS Quasi-Newton, Bayesian regularization, CG training algorithm with Polak-Ribiere update procedure then speeding suggested networks by modification these training algorithm, many of them having a very fast convergence rate for reasonable size networks. The above modify algorithms have a variety of different computation and storage requirements, however non of the above algorithms has a global properties, such as stability and convergence, which suited to all problems, and all the above algorithms applied in solving two point boundary value problem . Finally, we illustrate the suggested network by solving a variety of model problems and present comparisons with solutions obtained using other different method .

About the Author

Muna H. Ali has obtained her BSc in 2006 and MSc in 2012 from Baghdad University,EducationCollege Ibn Al-Haitham,Mathematics Department. Luma N. M. Tawfiq has obtained her Ph.D. drgree in the Artificial Neural Network andits applications in 2004