Data for TgNN

Figshare2019-10-24 更新2026-04-29 收录

地下水流模拟

物理信息神经网络

数据链接：

https://figshare.com/articles/dataset/Data_for_TgNN/10032980 数据链接链接失效反馈

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资源简介：

The data are the supporting materials for the paper 'Deep Learning of Subsurface Flow via Theory-guided Neural Network'.

创建时间：

2019-10-24

Cooper Basin Drawdown Calculations - De Glee method

地下水流模拟

煤层气开发环境影响

## **Abstract** \n\nThis dataset was derived by the Bioregional Assessment Programme. The parent datasets are identified in the Lineage field in this metadata statement. The process undertaken to prod

Research Data Australia60

GroMoPo Metadata for Mendha sub-basin model

地下水流模拟

水资源评估

A direct approach to designing MODFLOW finite difference model is tedious and less intuitive, specifically for complex boundary and initial conditions. Therefore, a MODFLOW model can be developed eith

DataONE2023-04-13 更新30

MODFLOW models for the simulation of groundwater-flow dynamics in the U.S. Northern High Plains driven by multi-model estimates of surficial aquifer recharge.

地下水流模拟

水资源管理

There is a growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including new...

data.gov00

GroMoPo Metadata for Madison Group, Powder River Basin USGS model

地下水流模拟

含水层可持续性

A digital simulation model was used to analyze regional ground-water flow in the Madison Group aquifer in the Powder River Basin in Montana and Wyoming and adjacent areas. Most recharge to the aquifer

DataONE2023-02-07 更新50

A Physics-Informed, Deep Double Reservoir Network for Forecasting Boundary Layer Velocity

边界层速度预测

物理信息神经网络

When a fluid flows over a solid surface, it creates a thin boundary layer where the flow velocity is influenced by the surface through viscosity, and can transition from laminar to turbulent at suffic

Taylor & Francis Group2024-12-03 更新20

Data for TgNN

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