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浏览/检索结果: 共71条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 An Improved Hybrid GC-LSTM Framework for Hourly Nowcasting of Ground-Level NO2 Concentrations Over Beijing-Tianjin-Hebei Region 期刊论文  OAI收割 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2025, 卷号: 63, 页码: 14 作者:  Han, Zongfu;  Fan, Meng;  Song, Shipeng;  Liang, Xiaoxia;  Song, Meina   |  收藏  |  浏览/下载：8/0  |  提交时间：2025/03/03 Atmospheric modeling  Monitoring  Predictive models  Satellites  Long short term memory  Forecasting  Accuracy  Air pollution  Spatial resolution  Graphical models  Grained cascade forest (gcForest)  ground-level nitrogen dioxide (NO2)  long short-term memory (LSTM)  nowcasting  tropospheric monitoring instrument (TROPOMI)   Comparing machine learning algorithms to predict vegetation fire detections in Pakistan 期刊论文  OAI收割 FIRE ECOLOGY, 2024, 卷号: 20, 期号: 1, 页码: 20 作者:  Shahzad, Fahad;  Mehmood, Kaleem;  Hussain, Khadim;  Haidar, Ijlal   |  收藏  |  浏览/下载：16/0  |  提交时间：2024/08/30 Machine learning  Forest fire  Crop fire  Other vegetation fire  Prediction models   Spatiotemporal variations of atmospheric nitrogen deposition in China during 2008-2020 期刊论文  OAI收割 ATMOSPHERIC ENVIRONMENT, 2023, 卷号: 315, 页码: 15 作者:  Chen, Shiliang;  Chen, Bin;  Wang, Shaoqiang;  Sun, Leigang;  Shi, Hao   |  收藏  |  浏览/下载：38/0  |  提交时间：2024/03/25 Random forest models  Reduced and oxidized nitrogen  NO (x )and SO (2 )emission  NH( 3 )emission  Atmospheric deposition  China   Susceptibility assessment of earth fissure related to groundwater extraction using machine learning methods combined with weights of evidence 期刊论文  OAI收割 NATURAL HAZARDS, 2023, 页码: 23 作者:  Wei, Aihua;  Chen, Yuanyao;  Zhao, Haijun;  Liu, Zhao;  Yang, Likui   |  收藏  |  浏览/下载：14/0  |  提交时间：2023/12/29 Earth fissure assessment  Weights of evidence  Support vector machine learning  Random forest  Ensemble models   A Comprehensive Prediction Method for Pore Pressure in Abnormally High-Pressure Blocks Based on Machine Learning 期刊论文  OAI收割 PROCESSES, 2023, 卷号: 11, 期号: 9, 页码: 31 作者:  Li, Huayang;  Tan, Qiang;  Deng, Jingen;  Dong, Baohong;  Li, Bojia   |  收藏  |  浏览/下载：2/0  |  提交时间：2025/06/27 pore pressure prediction  machine learning  KNN  Extra Trees  Random Forest  LightGBM  overpressure  well logs  empirical models   Learning ensembles of process-based models for high accurately evaluating the one-hundred-year carbon sink potential of China's forest ecosystem 期刊论文  OAI收割 HELIYON, 2023, 卷号: 9, 期号: 6, 页码: e17243 作者:  Wang, Zhaosheng;  Li, Renqiang;  Guo, Qingchun;  Wang, Zhaojun;  Huang, Mei   |  收藏  |  浏览/下载：36/0  |  提交时间：2023/09/07 Learning ensembles of process-based models  Random forest model  Forest ecosystem  Carbon sink potential   A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices 期刊论文  OAI收割 IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 3, 页码: 784-794 作者:  Yuan, Ye;  He, Qiang;  Luo, Xin;  Shang, Mingsheng   |  收藏  |  浏览/下载：53/0  |  提交时间：2022/08/22 Computational modeling  Sparse matrices  Big Data  Data models  Stochastic processes  Training  Software algorithms  Big data  latent factor analysis  generally multilayered structure  deep forest  multilayered extreme learning machine  randomized-learning  high-dimensional and sparse matrix  stochastic gradient descent  randomized model   Reflectance and chlorophyll fluorescence-based retrieval of photosynthetic parameters improves the estimation of subtropical forest productivity 期刊论文  OAI收割 ECOLOGICAL INDICATORS, 2021, 卷号: 131, 页码: 12 作者:  Amir, Muhammad;  Chen, Jinghua;  Chen, Bin;  Wang, Shaoqiang;  Zhu, Kai   |  收藏  |  浏览/下载：35/0  |  提交时间：2022/09/21 Forest  Gross primary production  Chlorophyll fluorescence  V-cmax  Ecosystem models   Reflectance and chlorophyll fluorescence-based retrieval of photosynthetic parameters improves the estimation of subtropical forest productivity 期刊论文  OAI收割 ECOLOGICAL INDICATORS, 2021, 卷号: 131, 页码: 12 作者:  Amir, Muhammad   |  收藏  |  浏览/下载：28/0  |  提交时间：2022/09/21 Forest  Gross primary production  Chlorophyll fluorescence  V-cmax  Ecosystem models   Online Multiview Deep Forest for Remote Sensing Image Classification via Data Fusion 期刊论文  OAI收割 IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 卷号: 18, 期号: 8, 页码: 1456-1460 作者:  Nie, Xiangli;  Gao, Ruofei;  Wang, Rui;  Xiang, Deliang   |  收藏  |  浏览/下载：44/0  |  提交时间：2021/11/02 Vegetation  Forestry  Random forests  Feature extraction  Remote sensing  Data models  Training data  Deep forest  online multiview learning  polarimetric synthetic aperture radar (PolSAR)  remote sensing data classification