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• 中国科学院大学 [2]
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• OAI收割 [33]
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筛选

浏览/检索结果: 共35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提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Soil moisture estimation based on FY-3E backscattering data for enhanced daily coverage to SMAP observations in the dawn-dusk orbit 期刊论文  OAI收割 REMOTE SENSING OF ENVIRONMENT, 2024, 卷号: 309, 页码: 114209 作者:  Song, Peilin;  Liu, Xiangzhuo;  Sun, Ling;  Zhai, Xiaochun;  Wang, Jiao   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/08/22 Soil moisture  Passive microwave  Active microwave  Water-cloud model  ASCAT   Formation of In-Cloud Aqueous-Phase Secondary Organic Matter and Related Characteristic Molecules 期刊论文  OAI收割 JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2024, 卷号: 129, 期号: 7, 页码: 13 作者:  Sun, Wei;  Zhang, Guohua;  Guo, Ziyong;  Fu, Yuzhen;  Peng, Xiaocong   |  收藏  |  浏览/下载：11/0  |  提交时间：2024/09/12 cloud water  aqueous-phase reaction  molecular composition  secondary organic aerosols  FT-ICR MS   Increased diurnal temperature range in global drylands in more recent decades 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2023, 页码: 13 作者:  Daramola, Mojolaoluwa T.;  Li, Renqiang;  Xu, Ming   |  收藏  |  浏览/下载：14/0  |  提交时间：2024/01/22 aridity gradient  asymmetric warming  cloud cover  daily maximum temperature  moisture flux  water vapour   In-cloud scavenging of chemically segregated particle types by individual particle observation 期刊论文  OAI收割 APPLIED GEOCHEMISTRY, 2023, 卷号: 152, 页码: 8 作者:  Yang, Yuxiang;  Peng, Xiaocong;  Zhang, Guohua;  Hu, Xiaodong;  Guo, Ziyong   |  收藏  |  浏览/下载：7/0  |  提交时间：2024/08/23 Single particle  In-cloud scavenging  Liquid water content  Mixing state   Cloud model driven assessment of interregional water ecological carrying capacity and analysis of its spatial-temporal collaborative relation 期刊论文  OAI收割 JOURNAL OF CLEANER PRODUCTION, 2023, 卷号: 384, 页码: 17 作者:  Yang, Lingzhi;  Chen, Yizhong;  Lu, Hongwei;  Qiao, Youfeng;  Peng, He   |  收藏  |  浏览/下载：25/0  |  提交时间：2023/02/06 Water ecological carrying capacity  Cloud model  Combination prediction  Spatial -temporal collaborative relation  Efficiency analysis   The Effect of Negative Samples on the Accuracy of Water Body Extraction Using Deep Learning Networks 期刊论文  OAI收割 REMOTE SENSING, 2023, 卷号: 15, 期号: 2, 页码: 17 作者:  Song, Jia;  Yan, Xiangbing   |  收藏  |  浏览/下载：19/0  |  提交时间：2023/02/27 water body extraction  deep learning  negative sample  cloud shadow interference  semantic segmentation   The Effect of Negative Samples on the Accuracy of Water Body Extraction Using Deep Learning Networks 期刊论文  OAI收割 REMOTE SENSING, 2023, 卷号: 15, 期号: 2, 页码: 17 作者:  Song, Jia;  Yan, Xiangbing   |  收藏  |  浏览/下载：16/0  |  提交时间：2023/02/27 water body extraction  deep learning  negative sample  cloud shadow interference  semantic segmentation   Technical note: Chemical composition and source identification offluorescent components in atmospheric water-soluble brown carbon byexcitation-emission matrix spectroscopy with parallel factor analysis - potentiallimitations and applications 期刊论文  OAI收割 ATMOSPHERIC CHEMISTRY AND PHYSICS, 2023, 卷号: 23, 期号: 4, 页码: 2613-2625 作者:  Cao, Tao;  Li, Meiju;  Xu, Cuncun;  Song, Jianzhong;  Fan, Xingjun   |  收藏  |  浏览/下载：10/0  |  提交时间：2024/09/26 DISSOLVED ORGANIC-MATTER  HUMIC-LIKE FLUORESCENCE  MOLECULAR CHARACTERIZATION  OPTICAL-PROPERTIES  AEROSOL-PARTICLES  LIGHT-ABSORPTION  CLOUD-WATER  FULVIC-LIKE  SUBSTANCES  CHEMISTRY   Revisiting the physical mechanisms of East Asian summer monsoon precipitation changes during the mid-Holocene: a data-model comparison 期刊论文  OAI收割 CLIMATE DYNAMICS, 2022, 页码: 14 作者:  Sun, Yong;  Wu, Haibin;  Ramstein, Gilles;  Liu, Bo;  Zhao, Yan   |  收藏  |  浏览/下载：44/0  |  提交时间：2022/07/19 Mid-Holocene  Monsoon precipitation  Data-model comparison  Water vapor budget  Thermodynamic effect  Dynamic effect  Cloud cooling effect   Cloud Computing Based Demand Response Management using Deep Reinforcement Learning 期刊论文  OAI收割 IEEE Transactions on Cloud Computing, 2022, 卷号: 10, 期号: 1, 页码: 72-81 作者:  Song CH(宋纯贺);  Han GJ(韩光洁);  Zeng P(曾鹏)   |  收藏  |  浏览/下载：23/0  |  提交时间：2021/12/05 Demand response  cloud computing  load aggregator  water heater  deep reinforcement learning