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| Landslide detection using visualization techniques for deep convolutional neural network models 期刊论文
Natural Hazards, 2021
作者: Hacıefendioğlu K.; Demir G.; Başağa H.B.
  收藏 | 浏览/下载：211/0 | 提交时间：2021/09/01
Convolutional neural networks Deep learning method GradCAM Inception-V3 Landslide Resnet-50 ScoreCAM VGG-19 |
| 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：233/0 | 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 |
| Deep reinforcement learning for the real time control of stormwater systems 期刊论文
, 2020, 卷号: 140
作者: Mullapudi A.; Lewis M.J.; Gruden C.L.; Kerkez B.
收藏 | 浏览/下载：35/0 | 提交时间：2020/07/28
Controllers Deep neural networks Learning systems Real time control Reinforcement learning Storms Water levels Autonomous control Computational resources Control performance Open source implementation Performance enhancements Stormwater systems Uncontrolled systems Urban stormwater systems Deep learning algorithm machine learning real time stormwater |
| 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：33/0 | 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 |
| Impact of deep learning-based dropout on shallow neural networks applied to stream temperature modelling 期刊论文
Earth Science Reviews, 2020, 卷号: 201
作者: Piotrowski A.P.; Napiorkowski J.J.; Piotrowska A.E.
收藏 | 浏览/下载：21/0 | 提交时间：2021/09/01
Atmosphere-hydrosphere interactions Deep learning Dropout Shallow artificial neural networks Stream temperature modelling |
| Inverse design of an integrated-nanophotonics optical neural network 期刊论文
Science Bulletin, 2020, 卷号: 65, 期号: 14
作者: Qu Y.; Zhu H.; Shen Y.; Zhang J.; Tao C.; Ghosh P.; Qiu M.
收藏 | 浏览/下载：26/0 | 提交时间：2021/09/01
Deep learning Integrated nanophotonics Inverse design Optical neural networks Silicon photonics |
| Graph attention convolutional neural network model for chemical poisoning of honey bees’ prediction 期刊论文
Science Bulletin, 2020, 卷号: 65, 期号: 14
作者: Wang F.; Yang J.-F.; Wang M.-Y.; Jia C.-Y.; Shi X.-X.; Hao G.-F.; Yang G.-F.
收藏 | 浏览/下载：31/0 | 提交时间：2021/09/01
Deep learning Graph attention convolutional neural networks Honey bees toxicity Molecular design Pesticide |
| A novel framework for daily forecasting of ozone mass concentrations based on cycle reservoir with regular jumps neural networks 期刊论文
ATMOSPHERIC ENVIRONMENT, 2020, 卷号: 220
作者: Mo Y.; Li Q.; Karimian H.; Fang S.; Tang B.; Chen G.; Sachdeva S.
收藏 | 浏览/下载：29/0 | 提交时间：2022/01/18
Air pollution Deep neural networks Machine learning Ozone Prediction Recurrent neural networks |
