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Tunnel geothermal disaster susceptibility evaluation based on interpretable ensemble learning: A case study in Ya'an-Changdu section of the Sichuan-Tibet traffic corridor 期刊论文
ENGINEERING GEOLOGY, 2023, 卷号: 313
作者:  Chen, Zhe;  Chang, Ruichun;  Pei, Xiangjun;  Yu, Zhengbo;  Guo, Huadong;  He, Ziqiong;  Zhao, Wenbo;  Zhang, Quanping;  Chen, Yu
收藏  |  浏览/下载：10/0  |  提交时间：2024/03/01
Interpretability  Ensemble learning  Tunnel geothermal disasters  Susceptibility evaluation  Sichuan-Tibet traffic corridor  
A data-driven approach to generate past GRACE-like terrestrial water storage solution by calibrating the land surface model simulations 期刊论文
, 2020, 卷号: 143
作者:  Jing W.;  Di L.;  Zhao X.;  Yao L.;  Xia X.;  Liu Y.;  Yang J.;  Li Y.;  Zhou C.
收藏  |  浏览/下载：35/0  |  提交时间：2020/07/28
Decision trees  Digital storage  Evapotranspiration  Geodetic satellites  Groundwater  Learning systems  Soil moisture  Surface measurement  Water conservation  Water supply  Data-driven approach  Ensemble learning algorithm  Gravity recovery and climate experiment satellites  Groundwater storage  Land surface modeling  Machine learning models  Terrestrial water storage  Variable importances  Learning algorithms  
Petrophysical characterization of deep saline aquifers for CO2 storage using ensemble smoother and deep convolutional autoencoder 期刊论文
, 2020, 卷号: 142
作者:  Liu M.;  Grana D.
收藏  |  浏览/下载：27/0  |  提交时间：2020/07/28
Aquifers  Boreholes  Carbon capture  Carbon dioxide  Convolution  Digital storage  Forecasting  Geological surveys  Hydrogeology  Inverse problems  Large dataset  Offshore oil well production  Petrophysics  Porosity  Seismology  Stochastic systems  Carbon dioxide sequestration  Deep saline aquifers  Ensemble-based method  Machine learning methods  Monitoring measurements  Petro-physical characterizations  Petrophysical properties  Stochastic approach  Learning systems  accuracy assessment  aquifer  carbon dioxide  carbon sequestration  carbon storage  leakage  monitoring  permeability  physical property  porosity  precision  underground storage  
Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale 期刊论文
, 2020, 卷号: 136
作者:  Papacharalampous G.;  Tyralis H.;  Koutsoyiannis D.;  Montanari A.
收藏  |  浏览/下载：19/0  |  提交时间：2020/07/28
Catchments  Climate models  Forecasting  Regression analysis  Uncertainty analysis  Ensemble learning  Hydrological modeling  Probabilistic prediction  Quantile averaging  Quantile regression  Uncertainty quantifications  Learning systems  catchment  experimental study  hydrological modeling  prediction  probability  quantitative analysis  regression analysis  time series analysis  timescale  uncertainty analysis  United States  
Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models 期刊论文
, 2020, 卷号: 136
作者:  Papacharalampous G.;  Koutsoyiannis D.;  Montanari A.
收藏  |  浏览/下载：22/0  |  提交时间：2020/07/28
Climate models  Forecasting  Hydrology  Regression analysis  Uncertainty analysis  Ensemble learning  Hydrological modeling  Probabilistic prediction  Quantile averaging  Quantile regression  Uncertainty quantifications  Learning systems  ensemble forecasting  error analysis  hydrological modeling  learning  model test  performance assessment  prediction  probability  quantitative analysis  uncertainty analysis  
Short-term rockburst risk prediction using ensemble learning methods 期刊论文
Natural Hazards, 2020, 卷号: 104, 期号: 2
作者:  Liang W.;  Sari A.;  Zhao G.;  McKinnon S.D.;  Wu H.
收藏  |  浏览/下载：18/0  |  提交时间：2021/09/01
Ensemble learning  Microseismic monitoring  Prediction  Rockburst  Short-term risk  
Modeling the multiple time scale response of hydrological drought to climate change in the data-scarce inland river basin of Northwest China 期刊论文
ARABIAN JOURNAL OF GEOSCIENCES, 2019, 卷号: 12, 期号: 7
作者:  Zhu, Nina;  Xu, Jianhua;  Wang, Chong;  Chen, Zhongsheng;  Luo, Yang
收藏  |  浏览/下载：40/0  |  提交时间：2019/10/08
Deep learning  Ensemble empirical mode decomposition  Hybrid model  Long short-term memory model  Simulation  Statistical downscaling  
Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems 期刊论文
JOURNAL OF HYDROLOGY, 2019, 卷号: 570
作者:  Wen, Xiaohu;  Feng, Qi;  Deo, Ravinesh C.;  Wu, Min;  Yin, Zhenliang;  Yang, Linshan;  Singh, Vijay P.
收藏  |  浏览/下载：49/0  |  提交时间：2019/11/08
Expert system  Runoff  Integrated model  Complete ensemble empirical mode decomposition adaptive noise (CEEMDAN)  Variational mode decomposition (VMD)  Extreme learning machine (ELM)