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Physics-Informed Neural Networks for Elliptical-Anisotropy Eikonal Tomography: Application to Data From the Northeastern Tibetan Plateau 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH, 2023, 卷号: 128, 期号: 12
作者:  Chen, Yunpeng;  de Ridder, Sjoerd A. L.;  Rost, Sebastian;  Guo, Zhen;  Wu, Xiaoyang;  Li, Shilin;  Chen, Yongshun
收藏  |  浏览/下载：17/0  |  提交时间：2024/03/01
elliptical-anisotropy eikonal tomography  anisotropy  physics informed neural network  deep learning  surface waves  Tibet  
Investigating the seasonal dynamics of surface water over the Qinghai-Tibet Plateau using Sentinel-1 imagery and a novel gated multiscale ConvNet 期刊论文
INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2023, 卷号: 16, 期号: 1
作者:  Luo, Xin;  Hu, Zhongwen;  Liu, Lin
收藏  |  浏览/下载：4/0  |  提交时间：2024/03/01
Qinghai-Tibet Plateau  surface water mapping  deep learning  convolutional neural network  SAR image  
Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport 期刊论文
, 2020, 卷号: 141
作者:  He Q.;  Barajas-Solano D.;  Tartakovsky G.;  Tartakovsky A.M.
收藏  |  浏览/下载：247/0  |  提交时间：2020/07/28
Deep neural networks  Hydraulic conductivity  Learning systems  Porous materials  State estimation  Accuracy of parameters  Computational costs  Concentration fields  Concentration Measurement  Data assimilation  Governing equations  Parameter and state estimation  Subsurface transport  Parameter estimation  artificial neural network  data assimilation  hydraulic conductivity  hydraulic head  porous medium  subsurface flow  transport process  
PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media 期刊论文
, 2020, 卷号: 138
作者:  Santos J.E.;  Xu D.;  Jo H.;  Landry C.J.;  Prodanović M.;  Pyrcz M.J.
收藏  |  浏览/下载：28/0  |  提交时间：2020/07/28
Binary images  Convolution  Deep learning  Deep neural networks  Flow fields  Flow of fluids  Forecasting  Learning systems  Mechanical permeability  Network architecture  Porous materials  Velocity  Disruptive technology  Fluid velocity field  Geometrical informations  Machine learning models  Orders of magnitude  Spatial relationships  Subsurface formations  Surrogate model  Convolutional neural networks  artificial neural network  digital image  flow modeling  fluid flow  permeability  porous medium  prediction  rock mechanics  surrogate method  three-dimensional modeling  
Seeing macro-dispersivity from hydraulic conductivity field with convolutional neural network 期刊论文
, 2020, 卷号: 138
作者:  Zhou Z.;  Shi L.;  Zha Y.
收藏  |  浏览/下载：34/0  |  提交时间：2020/07/28
Convolution  Deep learning  Deep neural networks  Groundwater  Groundwater pollution  Hydraulic conductivity  Learning algorithms  Learning systems  Porous materials  Solute transport  Contaminant transport  Convolutional neural work  Groundwater environment  Heterogeneity  Macrodispersivity  Quantitative relations  Spatial heterogeneity  Trained neural networks  Convolutional neural networks  algorithm  artificial neural network  computer simulation  groundwater  heterogeneity  hydraulic conductivity  machine learning  
Monitoring inland water quality using remote sensing: potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing 期刊论文
Earth Science Reviews, 2020, 卷号: 205
作者:  Sagan V.;  Peterson K.T.;  Maimaitijiang M.;  Sidike P.;  Sloan J.;  Greeling B.A.;  Maalouf S.;  Adams C.
收藏  |  浏览/下载：30/0  |  提交时间：2021/09/01
Cloud computing  Deep learning  Long short-term memory neural network  Remote sensing.  Water quality  
Assessing the effects of climate change on water quality of plateau deep-water lake - A study case of Hongfeng Lake 期刊论文
SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 卷号: 647, 页码: 1518-1530
作者:  Longyang, Qianqiu
收藏  |  浏览/下载：30/0  |  提交时间：2019/10/08
Climate change  Artificial neural network model  Deep-water lake  Eutrophication  Non-point pollution  
Deep Neural Networks for Curbing Climate Change-Induced Farmers-Herdsmen Clashes in a Sustainable Social Inclusion Initiative 期刊论文
PROBLEMY EKOROZWOJU, 2019, 卷号: 14, 期号: 2, 页码: 143-155
作者:  Okewu, Emmanuel;  Misra, Sanjay;  Fernandez Sanz, Luis;  Ayeni, Foluso;  Mbarika, Victor;  Damasevicius, Robertas
收藏  |  浏览/下载：32/0  |  提交时间：2019/10/08
climate change  deep neural network  farmers-herdsmen clashes  policies and programmes  social inclusion  
Detecting Climate Change Deniers on Twitter Using a Deep Neural Network 期刊论文
ICMLC 2019: 2019 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING, 2019, 页码: 204-210
作者:  Chen, Xingyu;  Zou, Lei;  Zhao, Bo
收藏  |  浏览/下载：34/0  |  提交时间：2019/10/08
Climate change  deep neural network  social media  Twitter