Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems
Book Details
Format
Hardback or Cased Book
ISBN-10
1032502983
ISBN-13
9781032502984
Publisher
Taylor & Francis Ltd
Imprint
CRC Press
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jul 6th, 2023
Print length
180 Pages
Weight
452 grams
Dimensions
16.20 x 24.10 x 1.70 cms
Product Classification:
Numerical analysisApplied mathematicsPhysicsMathematical / Computational / Theoretical physicsMathematical physicsLife sciences: general issuesDigital and Information technology: general topicsInformation technology: general issuesComputer scienceMachine learningNeural networks & fuzzy systemsNeural networks and fuzzy systems
Ksh 16,200.00
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This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.
This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.
Get Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Taylor & Francis Ltd and it has pages.
