研究论文
Modeling water flow in unsaturated soils through physics-informed neural network with principled loss function
Yang Chen, Yongfu Xu, Lei Wang, Tianyi Li
Shanghai Jiao Tong University Shanghai University of Engineering Science
来源Computers and Geotechnics
年份2023
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59
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7.50
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学术脉络
学科主题
物理Model Reduction and Neural Networks
Dam Engineering and Safety · Soil and Unsaturated Flow
参考文献 73
MODFLOW-2005 : the U.S. Geological Survey modular ground-water model--the ground-water flow process
被引 2,166Arlen W. Harbaugh · Techniques and methods · 2005
Understanding the difficulty of training deep feedforward neural networks
被引 12,674Xavier Glorot, Yoshua Bengio · 2010
Early Stopping — But When?
被引 968Lutz Prechelt · Lecture notes in computer science · 2012
此处列出前 3 条
引用本文 59
Physics-informed machine learning in geotechnical engineering: a direction paper
被引 67Biao Yuan, Chung Siung Choo, Lit Yen Yeo · Geomechanics and Geoengineering · 2025
Machine learning in concrete durability: challenges and pathways identified by RILEM TC 315-DCS towards enhanced predictive models
被引 41Woubishet Zewdu Taffese, Benoît Hilloulin, Yury Villagrán Zaccardi · Materials and Structures · 2025
A novel physics-informed deep learning strategy with local time-updating discrete scheme for multi-dimensional forward and inverse consolidation problems
被引 39Hongwei Guo, Zhen‐Yu Yin · Computer Methods in Applied Mechanics and Engineering · 2024
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