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Earthquake Catalog-Based Machine Learning Identification of Laboratory Fault States and the Effects of Magnitude of Completeness 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2018, 45 (24) : 13269-13276
作者:  Lubbers, Nicholas;  Bolton, David C.;  Mohd-Yusof, Jamaludin;  Marone, Chris;  Barros, Kipton;  Johnson, Paul A.
收藏  |  浏览/下载：8/0  |  提交时间：2019/04/09
machine learning  laboratory earthquakes  earthquake catalogs  earthquake forecasting  magnitude of completeness  
Estimating Regional Ground-Level PM2.5 Directly From Satellite Top-Of-Atmosphere Reflectance Using Deep Belief Networks 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2018, 123 (24) : 13875-13886
作者:  Shen, Huanfeng;  Li, Tongwen;  Yuan, Qiangqiang;  Zhang, Liangpei
收藏  |  浏览/下载：9/0  |  提交时间：2019/04/09
PM2  5  satellite remote sensing  TOA reflectance  deep learning  
A Versatile Method for Ice Particle Habit Classification Using Airborne Imaging Probe Data 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2018, 123 (23) : 13472-13495
作者:  Praz, C.;  Ding, S.;  McFarquhar, G. M.;  Berne, A.
收藏  |  浏览/下载：5/0  |  提交时间：2019/04/09
ice crystal  habit classification  optical array probe  machine learning  logistic regression  cloud microphysics  
Quantifying driving factors of vegetation carbon stocks of Moso bamboo forests using machine learning algorithm combined with structural equation model 期刊论文
FOREST ECOLOGY AND MANAGEMENT, 2018, 429: 406-413
作者:  Shi, Yongjun;  Xu, Lin;  Zhou, Yufeng;  Ji, Biyong;  Zhou, Guomo;  Fang, Huiyun;  Yin, Jiayang;  Deng, Xu
收藏  |  浏览/下载：8/0  |  提交时间：2019/04/09
Vegetation carbon stocks  Carbon sequestration  Driving factors  Machine learning method  Structural equation modeling  Phyllostachys pubescens  
Toward Data-Driven Weather and Climate Forecasting: Approximating a Simple General Circulation Model With Deep Learning 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2018, 45 (22) : 12616-12622
作者:  Scher, S.
收藏  |  浏览/下载：1/0  |  提交时间：2019/04/09
machine learning  weather prediction  neural networks  deep learning  climate models  
Response to Comment on "Predicting reaction performance in C-N cross-coupling using machine learning" 期刊论文
SCIENCE, 2018, 362 (6416)
作者:  Estrada, Jesus G.;  Ahneman, Derek T.;  Sheridan, Robert P.;  Dreher, Spencer D.;  Doyle, Abigail G.
收藏  |  浏览/下载：4/0  |  提交时间：2019/11/27
Predictability of Extreme Precipitation in Western US Watersheds Based on Atmospheric River Occurrence, Intensity, and Duration 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2018, 45 (21) : 11693-11701
作者:  Chen, Xiaodong;  Leung, L. Ruby;  Gao, Yang;  Liu, Ying;  Wigmosta, Mark;  Richmond, Marshall
收藏  |  浏览/下载：4/0  |  提交时间：2019/04/09
Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2018, 38 (13) : 4891-4902
作者:  Wang, Bin;  Zheng, Lihong;  Liu, De Li;  Ji, Fei;  Clark, Anthony;  Yu, Qiang
收藏  |  浏览/下载：5/0  |  提交时间：2019/04/09
GCMs  machine learning  multi-model ensemble  random forest  support vector machine  
Comparison of different wind data interpolation methods for a region with complex terrain in Central Asia 期刊论文
CLIMATE DYNAMICS, 2018, 51: 3635-3652
作者:  Reinhardt, Katja;  Samimi, Cyrus
收藏  |  浏览/下载：5/0  |  提交时间：2019/04/09
Spatial interpolation  Wind  Central Asia  Complex topography  
Machine learning methods for crop yield prediction and climate change impact assessment in agriculture 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2018, 13 (11)
作者:  Crane-Droesch, Andrew
收藏  |  浏览/下载：3/0  |  提交时间：2019/04/09
agriculture  machine learning  climate change impacts