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• OAI收割 [18]

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浏览/检索结果: 共18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 A multi-source data fusion method for land cover production: a case study of the East European Plain 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2024, 卷号: 17, 期号: 1, 页码: 18 作者:  Li, Kai;  Wang, Juanle   |  收藏  |  浏览/下载：56/0  |  提交时间：2024/05/06 Land cover  East European Plain  multi-source data fusion  deep learning   Research on the Exposure Risk Analysis of Wildfires with a Spatiotemporal Knowledge Graph 期刊论文  OAI收割 FIRE-SWITZERLAND, 2024, 卷号: 7, 期号: 4, 页码: 22 作者:  Ge, Xingtong;  Peng, Ling;  Yang, Yi;  Wang, Yinda;  Chen, Deyue   |  收藏  |  浏览/下载：9/0  |  提交时间：2024/05/30 exposure risk analysis knowledge graph  multi-source data fusion  exposure risk analysis  spatiotemporal data   Study on the Weak Interlayer Identification Method Based on Borehole Photo-Acoustic Combined Measurement: Application to a Landslide Case Study 期刊论文  OAI收割 APPLIED SCIENCES-BASEL, 2022, 卷号: 12, 期号: 20 作者:  Wang, Jinchao;  Huang, Junfeng;  Min, Hui;  Wang, Feng;  Wang, Yiteng   |  收藏  |  浏览/下载：19/0  |  提交时间：2023/08/02 photo-acoustic combination measurement  weak interlayer  multi-source data fusion  borehole data visualization  borehole image processing   Disaster Prediction Knowledge Graph Based on Multi-Source Spatio-Temporal Information 期刊论文  OAI收割 Remote Sensing, 2022, 期号: 14, 页码: 1214 作者:  Ge, Xingtong;  Yang, Yi;  Chen, Jiahui;  Li, Weichao;  Huang, Zhisheng   |  收藏  |  浏览/下载：31/0  |  提交时间：2022/03/31 disaster prediction knowledge graph  spatio-temporal  disaster dynamic prediction  multi-source data fusion  forest fire risk prediction  geological landslide risk prediction   Long Time-Series Mapping and Change Detection of Coastal Zone Land Use Based on Google Earth Engine and Multi-Source Data Fusion 期刊论文  OAI收割 REMOTE SENSING, 2022, 卷号: 14, 期号: 1, 页码: 14 作者:  Chen, Dong;  Wang, Yafei;  Shen, Zhenyu;  Liao, Jinfeng;  Chen, Jiezhi   |  收藏  |  浏览/下载：35/0  |  提交时间：2022/09/21 coastal zone  land use  time series  multi-source data fusion  random forest  classification  change detection  reclamation  aquaculture   Long Time-Series Mapping and Change Detection of Coastal Zone Land Use Based on Google Earth Engine and Multi-Source Data Fusion 期刊论文  OAI收割 REMOTE SENSING, 2022, 卷号: 14, 期号: 1, 页码: 14 作者:  Chen, Dong;  Wang, Yafei;  Shen, Zhenyu;  Liao, Jinfeng;  Chen, Jiezhi   |  收藏  |  浏览/下载：33/0  |  提交时间：2022/09/21 coastal zone  land use  time series  multi-source data fusion  random forest  classification  change detection  reclamation  aquaculture   Characteristics of Global Ocean Abnormal Mesoscale Eddies Derived From the Fusion of Sea Surface Height and Temperature Data by Deep Learning 期刊论文  OAI收割 GEOPHYSICAL RESEARCH LETTERS, 2021, 卷号: 48, 期号: 17, 页码: 11 作者:  Liu, Yingjie;  Zheng, Quanan;  Li, Xiaofeng   |  收藏  |  浏览/下载：27/0  |  提交时间：2021/11/30 meososcale eddies  abnormal eddies  multi-source remote sensing data  deep learning  data fusion  statistical analysis of spatiotemporal characteristics   A multi-source data fusion modeling method for debris flow prevention engineering 期刊论文  OAI收割 JOURNAL OF MOUNTAIN SCIENCE, 2021, 卷号: 18, 期号: 4, 页码: 1049-1061 作者:  Xu Qing-yang;  Ye Jian;  Lyu Yi-jie   |  收藏  |  浏览/下载：9/0  |  提交时间：2023/08/23 Debris flow prevention  Level of detail  Debris flow simulation  Multi platform fusion  Multi source data fusion   Modeling the Carbon Cycle of a Subtropical Chinese Fir Plantation Using a Multi-Source Data Fusion Approach 期刊论文  OAI收割 FORESTS, 2020, 卷号: 11, 期号: 4, 页码: 16 作者:  Hu, Longwei;  He, Honglin;  Shen, Yan;  Ren, Xiaoli;  Yan, Shao-kui   |  收藏  |  浏览/下载：32/0  |  提交时间：2021/03/23 process-based terrestrial ecosystem model  model-data fusion  multi-source data  carbon cycle  plantation   A data-driven decision-making optimization approach for inconsistent lithium-ion cell screening 期刊论文  OAI收割 JOURNAL OF INTELLIGENT MANUFACTURING, 2020, 卷号: 31, 期号: 4, 页码: 833-845 作者:  Liu, Chengbao;  Tan, Jie;  Wang, Xuelei   |  收藏  |  浏览/下载：33/0  |  提交时间：2020/06/02 Multi-source data fusion  Imbalanced learning  Convolutional auto-encoder  Generative adversarial networks  Inconsistent lithium-ion cell screening