A transfer learning physics-informed deep learning framework for modeling multiple solute dynamics in unsaturated soils
Modeling subsurface flow and transport phenomena is essential for addressing a wide
range of challenges in engineering, hydrology, and ecology. The Richards equation is a …
range of challenges in engineering, hydrology, and ecology. The Richards equation is a …
Flow prediction of heterogeneous nanoporous media based on physical information neural network
The simulation and prediction of fluid flow in porous media play a profoundly significant role
in today's scientific and engineering domains, particularly in gaining a deeper …
in today's scientific and engineering domains, particularly in gaining a deeper …
[HTML][HTML] Ensemble learning of soil–water characteristic curve for unsaturated seepage using physics-informed neural networks
The determination of the soil–water characteristic curve (SWCC) is crucial for hydro-
mechanical modelling and analysis of soil slopes. Conventional inverse analysis often relies …
mechanical modelling and analysis of soil slopes. Conventional inverse analysis often relies …
Encoder–Decoder Convolutional Neural Networks for Flow Modeling in Unsaturated Porous Media: Forward and Inverse Approaches
The computational cost of approximating the Richards equation for water flow in unsaturated
porous media is a major challenge, especially for tasks that require repetitive simulations …
porous media is a major challenge, especially for tasks that require repetitive simulations …
TAMHA-DDPM: A Time-Aware Multi-Head Attention Denoising Diffusion Probability Model for Fuzzy Data Optimization in Intelligent Transportation Systems
S Mu, B Liu, J Gu, C Lien, X Chen - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the planning and decision making of transport systems, data relationships are complex
and the eigenvalues of data samples may contain errors, resulting in traffic fuzzy data. Traffic …
and the eigenvalues of data samples may contain errors, resulting in traffic fuzzy data. Traffic …
Principal Component Analysis for Equation Discovery
Principal Component Analysis (PCA) is one of the most commonly used statistical methods
for data exploration, and for dimensionality reduction wherein the first few principal …
for data exploration, and for dimensionality reduction wherein the first few principal …