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Combining statistical machine learning models with ARIMA for water level forecasting: The case of the Red river 期刊论文
, 2020, 卷号: 142
作者:  Phan T.-T.-H.;  Nguyen X.H.
收藏  |  浏览/下载：26/0  |  提交时间：2020/07/28
Autoregressive moving average model  Cost effectiveness  Disaster prevention  Forecasting  Learning algorithms  Water levels  Water resources  Auto-regressive integrated moving average  Computational time  Cost-effective solutions  Linear and nonlinear models  Physically based models  Statistical machine learning  Time series forecasting  Water level forecasting  Machine learning  data set  flood forecasting  forecasting method  hydrological modeling  machine learning  numerical model  performance assessment  river water  water level  Hanoi  Red River [Asia]  Viet Nam  
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：36/0  |  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  
Identifying relevant hydrological and catchment properties in active subspaces: An inference study of a lumped karst aquifer model 期刊论文
, 2020, 卷号: 135
作者:  Bittner D.;  Parente M.T.;  Mattis S.;  Wohlmuth B.;  Chiogna G.
收藏  |  浏览/下载：39/0  |  提交时间：2020/07/28
Aquifers  Catchments  Discharge (fluid mechanics)  Hydrogeology  Landforms  Runoff  Uncertainty analysis  Active subspaces  Catchment characteristics  Catchment properties  Computational performance  Dimension reduction  Hydrological properties  Karst hydrology  Rainfall-discharge  Sensitivity analysis  aquifer  catchment  discharge  geometry  hydrological modeling  karst hydrology  machine learning  sensitivity analysis  
Performance Evaluation of an Active PCM Thermal Energy Storage System for Space Cooling in Residential Buildings 期刊论文
, 2019, 卷号: 23, 期号: 2
作者:  Rucevskis S.;  Akishin P.;  Korjakins A.
收藏  |  浏览/下载：21/0  |  提交时间：2020/07/28
computational fluid dynamics  computer simulation  cooling  indoor air  numerical model  performance assessment  residential location  Baltic States