机构

• 地理科学与资源研究... [11]
• 力学研究所 [7]
• 数学与系统科学研究院 [4]
• 地质与地球物理研究所 [2]
• 理论物理研究所 [1]
• 大连化学物理研究所 [1]
• 更多

采集方式

• OAI收割 [32]
• iSwitch采集 [1]

内容类型

• 期刊论文 [31]
• SCI/SSCI论文 [2]

发表日期

• 2026 [1]
• 2025 [1]
• 2024 [3]
• 2023 [2]
• 2022 [5]
• 2021 [5]
• 更多

学科主题

• Physics [1]

筛选

浏览/检索结果: 共33条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择作者升序作者降序发表日期升序发表日期降序题名升序题名降序提交时间升序提交时间降序 Predicting distribution characteristics of PM2.5 concentrations across China combining land use regression model and spatiotemporally weighted stacking machine learning algorithms 期刊论文  OAI收割 JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING, 2026, 卷号: 14, 期号: 2, 页码: 121780 作者:  Wang, Wentao;  Zhang, Ping;  Han, Yuanyuan;  Zhang, Fengqian;  Huang, Yue   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/03/16 PM 2.5 pollution  Land use regression model  Machine learning ensemble method  Space-time weighting information  Spatiotemporal modelling   A framework for learning symbolic turbulence models from indirect observation data via neural networks and feature importance analysis 期刊论文  OAI收割 JOURNAL OF COMPUTATIONAL PHYSICS, 2025, 卷号: 537, 页码: 22 作者:  Wu CT(吴楚畋);  Zhang XL(张鑫磊);  Xu D(徐多);  He GW(何国威)   |  收藏  |  浏览/下载：14/0  |  提交时间：2025/08/18 Turbulence model  Ensemble Kalman method  Symbolic regression  Feature importance analysis  Neural networks   Optimal sensor placement for ensemble-based data assimilation using gradient-weighted class activation mapping 期刊论文  OAI收割 JOURNAL OF COMPUTATIONAL PHYSICS, 2024, 卷号: 514, 页码: 20 作者:  Xu ZY(许昭越);  Wang SZ(王士召);  Zhang XL(张鑫磊);  He GW(何国威)   |  收藏  |  浏览/下载：38/0  |  提交时间：2024/08/12 Optimal sensor placement  GradCAM  CNN  Ensemble Kalman method   Parallel ensemble Kalman method with total variation regularization for large-scale field inversion 期刊论文  OAI收割 JOURNAL OF COMPUTATIONAL PHYSICS, 2024, 卷号: 509, 页码: 18 作者:  Zhang XL(张鑫磊);  Zhang L(张磊);  He GW(何国威)   |  收藏  |  浏览/下载：36/0  |  提交时间：2024/07/04 Ensemble Kalman method  Parallel implementation  Field inversion  Data assimilation  Machine learning   Data augmented prediction of Reynolds stresses for flows around an axisymmetric body of revolution 期刊论文  OAI收割 OCEAN ENGINEERING, 2024, 卷号: 296, 页码: 14 作者:  Liu, Yi;  Wang, Shizhao;  Zhang, Xin-Lei;  He, Guowei;  He GW(何国威)   |  收藏  |  浏览/下载：237/0  |  提交时间：2024/05/21 Ensemble Kalman method  Machine learning  Turbulence modeling  SUBOFF model   Explainability analysis of neural network-based turbulence modeling for transonic axial compressor rotor flows 期刊论文  OAI收割 AEROSPACE SCIENCE AND TECHNOLOGY, 2023, 卷号: 141, 页码: 108542 作者:  Wu CT(吴楚畋);  Wang SZ(王士召);  Zhang XL(张鑫磊);  He GW(何国威)   |  收藏  |  浏览/下载：59/0  |  提交时间：2023/09/26 Explainability  Ensemble Kalman method  Turbulence model  Axial compressor rotor  Neural network  Machine learning   Combining direct and indirect sparse data for learning generalizable turbulence models 期刊论文  OAI收割 JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 卷号: 489, 页码: 112272 作者:  Zhang XL(张鑫磊);  Xiao, Heng;  Luo, Xiaodong;  He GW(何国威)   |  收藏  |  浏览/下载：48/0  |  提交时间：2023/09/05 Ensemble Kalman method  Turbulence modeling  Direct data  Indirect data   Estimating Vegetation Greening Influences on Runoff Signatures Using a Log-Based Weighted Ensemble Method 期刊论文  OAI收割 WATER RESOURCES RESEARCH, 2022, 卷号: 58, 期号: 12, 页码: 26 作者:  Huang, Qi;  Zhang, Yongqiang;  Ma, Ning;  Post, David   |  收藏  |  浏览/下载：36/0  |  提交时间：2023/03/20 vegetation greening  log-based weighted ensemble method  runoff signature  leaf area index change  the Yellow River basin   Trend Analysis and Driving Factors of Vegetation Dynamics in Northern China from 1982 to 2015 期刊论文  OAI收割 REMOTE SENSING, 2022, 卷号: 14, 期号: 23, 页码: 22 作者:  Sun, Rui;  Chen, Shaohui;  Su, Hongbo   |  收藏  |  浏览/下载：48/0  |  提交时间：2023/01/13 GIMMS NDVI3g  vegetation growth  ensemble empirical mode decomposition (EEMD) method  climate change  human activities   Trend Analysis and Driving Factors of Vegetation Dynamics in Northern China from 1982 to 2015 期刊论文  OAI收割 REMOTE SENSING, 2022, 卷号: 14, 期号: 23, 页码: 22 作者:  Sun, Rui;  Chen, Shaohui;  Su, Hongbo   |  收藏  |  浏览/下载：67/0  |  提交时间：2023/01/13 GIMMS NDVI3g  vegetation growth  ensemble empirical mode decomposition (EEMD) method  climate change  human activities