SpringerBriefs in Computational Intelligence

An Introduction to Neural Network Methods for Differential Equations

Authors: Yadav, Neha, Yadav, Anupam, Kumar, Manoj

Free Preview

Buy this book

eBook $24.99
$54.99 (listprice)
price for USA in USD (gross)
valid through June 30, 2019
  • ISBN 978-94-017-9816-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $34.99
$69.99 (listprice)
price for USA in USD
valid through June 30, 2019
  • ISBN 978-94-017-9815-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications.

The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multilayer perceptron and its learning methods. In Section IV, the different neural network methods for solving differential equations are introduced, including discussion of the most recent developments in the field.

Advanced students and researchers in mathematics, computer science and various disciplines in science and engineering will find this book a valuable reference source.

About the authors

Dr. Neha Yadav, Assistant Professor (Mathematics), Department of Applied Science, ITM University Gurgaon, Haryana-122017, India. Specialization: Numerical Analysis and Soft Computing Techniques, Differential Equations, Boundary Value Problems. Total Experience: 03 Years Teaching and 04 years Research Experience. Research Papers in Refereed SCI journals : 03 (Published), 03 (Submitted). Awards and Prizes: (i) Travel Award from CSIR-HRDG and NBHM (Govt. of India) to visit University of Strathclyde, Glasgow, U.K. in the year 2013. (ii) Qualified UGC-NET JRF in the year 2010. (iii) Selected for half financial to participate in “School and Conference on Computation Methods in Dynamics” at Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, from 20 June to 8 July 2011. (iv) Selected for MHRD Institute Fellowship in PhD at MNNIT Allahabad. (v) Selected for Summer Research Fellowship Programme jointly sponsored by IASc (Bangalore), INSA(New Delhi) and NASI(Allahabad).

Dr. Anupam Yadav, Assistant Professor (Mathematics). National Institute of Technology Uttarakhand. Pauri Garhwal, Uttarakhand - 246174. Specialization: Soft Computing Techniques, Swarm Intelligence, Artificial Intelligence. Area of Research: Optimization, Operations Research. Research Papers in Refereed SCI journals : 04 (Published), 04 (Submitted). Awards: Award from NBHM-DAE (Govt. of India) to visit Glasgow, U. K. in the year 2013. Award from CSIR-HRDG (Govt. Of India) to visit Taipei, Taiwan in the year 2011. CSIR – JRF (Mathematical Sciences) in the year 2009. GATE – 2009 with All India Rank 95. Positions held: Asst. Professor National Institute of Technology Uttarakhand, India. Research Professor: DPST Center, Korea University, Seoul, South Korea. Senior Research Fellow: IIT Roorkee, India. Junior Research Fellow: IIT Roorkee, India.

Dr. Manoj Kumar, Associate Professor (Mathematics), Motilal Nehru National Institute of Technology, Allahabad, India-211004. Specializations: Numerical Analysis and Computer Application, Simulation & Modeling. Area of Research: Numerical Analysis/Operation Research/Mathematical Modeling/Partial Differential Equations/ Computational Fluid Dynamics. Teaching Experience : Since 2001 teaching B.Tech, M.Tech, MCA classes and guiding PhD/ Post-Doctoral Students. Research Papers in Refereed SCI Journals:  67. PhD Student Guided: 09 (Awarded) , 02(Work in Progress). Post-Doctoral Guidance:04. Independent Research Grants: 04. Reviewer of International Journals: 11.

Reviews

“The book is intended to enable the reader to get an image on the variety of NN and the NN methods can be used in solving differential equations. It is a valuable reference material both from the presentation point of view and the provided references.” (Liviu Goraş, zbMATH 1328.92006, 2016)


Table of contents (4 chapters)

Table of contents (4 chapters)

Buy this book

eBook $24.99
$54.99 (listprice)
price for USA in USD (gross)
valid through June 30, 2019
  • ISBN 978-94-017-9816-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $34.99
$69.99 (listprice)
price for USA in USD
valid through June 30, 2019
  • ISBN 978-94-017-9815-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
An Introduction to Neural Network Methods for Differential Equations
Authors
Series Title
SpringerBriefs in Computational Intelligence
Copyright
2015
Publisher
Springer Netherlands
Copyright Holder
The Author(s)
eBook ISBN
978-94-017-9816-7
DOI
10.1007/978-94-017-9816-7
Softcover ISBN
978-94-017-9815-0
Series ISSN
2625-3704
Edition Number
1
Number of Pages
XIII, 114
Number of Illustrations
21 b/w illustrations
Topics