Effect of Data Pre-Processing on the Performance of Neural Networks for 1-D Transient Electromagnetic Forward Modeling

Effect of Data Pre-Processing on the Performance of Neural Networks for 1-D Transient Electromagnetic Forward Modeling

Geophysical modelling and data inversion are important tools for interpreting the physical properties of Earth's subsurface. Solving the inverse problem involves several computational steps and is generally a time consuming task. Artificial neural networks have the potential to speed up large c...

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Bibliographic Details
Main Authors: Muhammad Rizwan Asif, Thue S. Bording, Adrian S. Barfod, Denys J. Grombacher, Pradip K. Maurya, Anders V. Christiansen, Esben Auken, Jakob J. Larsen
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Data normalization
data pre-processing
forward modelling
inverse modelling
neural networks
Online Access:https://ieeexplore.ieee.org/document/9361672/

Internet

https://ieeexplore.ieee.org/document/9361672/

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