Multiphysics‐Informed Neural Networks for Coupled Soil Hydrothermal Modeling-Reference-Cited by-同舟云学术

Multiphysics‐Informed Neural Networks for Coupled Soil Hydrothermal Modeling

Published:2023-01 Issue:1 Volume:59 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resources Research

Author:

Wang Yanling¹,Shi Liangsheng¹^ORCID,Hu Xiaolong¹,Song Wenxiang¹^ORCID,Wang Lijun¹

Affiliation:

1. State Key Laboratory of Water Resources and Hydropower Engineering Sciences Wuhan University Wuhan China

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022WR031960

Reference50 articles.

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2. Identification of a hidden thermal fissure in a volcanic terrain using a combination of hydrothermal convection indicators and soil-atmosphere analysis

3. Physics‐Informed Neural Networks With Monotonicity Constraints for Richardson‐Richards Equation: Estimation of Constitutive Relationships and Soil Water Flux Density From Volumetric Water Content Measurements

4. Numerical solution of inverse problems by weak adversarial networks

5. Buckingham E.(1907).Studies on the movement of soil moisture.

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