研究论文
Reconstructing unsaturated infiltration behavior with sparse data via physics-informed deep learning
Peng Lan, Jing-Jing Su, Shuairun Zhu, Jinsong Huang, Sheng Zhang
Central South University University of Newcastle Australia Shanghai Ocean University
来源Computers and Geotechnics
年份2024
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逐年被引趋势
1790
24
1725
26
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36
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6.33
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同类平均 = 1
同类平均 = 1
前 2%
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同领域 · 同年份 · 同类型
74
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学术脉络
学科主题
工程Soil and Unsaturated Flow
Model Reduction and Neural Networks · Groundwater flow and contamination studies
参考文献 74
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
被引 2,669Yarin Gal, Zoubin Ghahramani · arXiv (Cornell University) · 2015
Hydraulic properties of porous media
被引 5,354R. H. Brooks, A. T. Corey · Digital Collections of Colorado (Colorado State University) · 1963
Adam: A Method for Stochastic Optimization
被引 84,700Diederik P. Kingma, Jimmy Ba · UvA-DARE (University of Amsterdam) · 2014
此处列出前 3 条
引用本文 36
Physics-informed machine learning in geotechnical engineering: a direction paper
被引 67Biao Yuan, Chung Siung Choo, Lit Yen Yeo · Geomechanics and Geoengineering · 2025
A rapid unsaturated infiltration prediction method for slope stability analysis considering uncertainties: Deep operator networks
被引 27Peng Lan, Jinsong Huang, Jingjing Su · Engineering Geology · 2025
Ensemble learning of soil–water characteristic curve for unsaturated seepage using physics-informed neural networks
被引 14Haoqing Yang, Chao Shi, Lulu Zhang · SOILS AND FOUNDATIONS · 2024
按被引量排序，此处列出前 3 条