Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems
Author:   Yinpeng Wang ,  Qiang Ren
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032503035


Pages:   180
Publication Date:   30 January 2025
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Our Price $94.99 Quantity:  
Add to Cart

Share |

Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems


Overview

Full Product Details

Author:   Yinpeng Wang ,  Qiang Ren
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   0.358kg
ISBN:  

9781032503035


ISBN 10:   1032503033
Pages:   180
Publication Date:   30 January 2025
Audience:   General/trade ,  College/higher education ,  Professional and scholarly ,  General ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1. Deep Learning Framework and Paradigm in Computational Physics 2. Application of U-net in 3D Steady Heat Conduction Solver 3. Inversion of complex surface heat flux based on ConvLSTM 4. Time-domain electromagnetic inverse scattering based on deep learning 5. Reconstruction of thermophysical parameters based on deep learning 6. Advanced Deep Learning Techniques in Computational Physics

Reviews

Author Information

Yinpeng Wang received the B.S. degree in Electronic and Information Engineering from Beihang University, Beijing, China in 2020, where he is currently pursuing his M.S. degree in Electronic Science and Technology. Mr. Wang focuses on the research of electromagnetic scattering, inverse scattering, heat transfer, computational multi-physical fields, and deep learning. Qiang Ren received the B.S. and M.S. degrees both in electrical engineering from Beihang University, Beijing, China, and Institute of Acoustics, Chinese Academy of Sciences, Beijing, China in 2008 and 2011, respectively, and the PhD degree in Electrical Engineering from Duke University, Durham, NC, in 2015. From 2016 to 2017, he was a postdoctoral researcher with the Computational Electromagnetics and Antennas Research Laboratory (CEARL) of the Pennsylvania State University, University Park, PA. In September 2017, he joined the School of Electronics and Information Engineering, Beihang University as an ""Excellent Hundred"" Associate Professor.

Tab Content 6

Author Website:  

Countries Available

All regions
Latest Reading Guide

NOV RG 20252

 

Shopping Cart
Your cart is empty
 Shopping cart
Mailing List

 

Sign up now