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科研机构

地理科学与资源研究所 [4]

北京航空航天大学 [3]

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武汉大学 [3]

海洋研究所 [2]

兰州理工大学 [1]

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	Graph-Based Memory Recall Recurrent Neural Network for Mid-Term Sea-Surface Height Anomaly Forecasting 期刊论文 IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 卷号: 17, 页码: 6642-6657 作者: Zhou, Yuan; Ren, Tian; Chen, Keran; Gao, Le; Li, Xiaofeng 收藏 \| 浏览/下载：0/0 \| 提交时间：2024/06/04 Forecasting Predictive models Atmospheric waves Spatiotemporal phenomena Sea surface Ocean waves Data models Sea-surface height anomaly (SSHA) deep learning (DL) spatiotemporal prediction Rossby waves
	A Spatial-Temporal Approach for Multi-Airport Traffic Flow Prediction Through Causality Graphs 期刊论文 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 页码: 13 作者: Du, Wenbo; Chen, Shenwen; Li, Zhishuai; Cao, Xianbin; Lv, Yisheng 收藏 \| 浏览/下载：4/0 \| 提交时间：2023/11/16 Airport traffic flow predictive models deep learning causality graph spatiotemporal analysis
	A Spatiotemporal Hybrid Model for Airspace Complexity Prediction 期刊论文 IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2022, 页码: 8 作者: Du, Wenbo; Li, Biyue; Chen, Jun; Lv, Yisheng; Li, Yumeng 收藏 \| 浏览/下载：15/0 \| 提交时间：2022/11/14 Complexity theory Atmospheric modeling Spatiotemporal phenomena Predictive models Deep learning Correlation Air traffic control
	A combined traffic flow forecasting model based on graph convolutional network and attention mechanism 期刊论文 INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2021, 卷号: 32, 期号: 12 作者: Zhang, Hong; Chen, Linlong; Cao, Jie; Zhang, Xijun; Kan, Sunan 收藏 \| 浏览/下载：13/0 \| 提交时间：2022/03/01 Traffic flow forecasting deep learning attention mechanism graph convolutional network spatiotemporal characteristics
	Traffic Forecasting via Dilated Temporal Convolution With Peak-Sensitive Loss 期刊论文 IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2021, 页码: 10 作者: Guo, Ge; Yuan, Wei; Liu, Jinyuan; Lv, Yisheng; Liu, Wei 收藏 \| 浏览/下载：20/0 \| 提交时间：2022/01/27 Correlation Spatiotemporal phenomena Forecasting Data models Deep learning Convolution Predictive models
	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 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：26/0 \| 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
	Encoder-Decoder Full Residual Deep Networks for Robust Regression and Spatiotemporal Estimation 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 9, 页码: 4217-4230 作者: Li, Lianfa; Fang, Ying; Wu, Jun; Wang, Jinfeng; Ge, Yong 收藏 \| 浏览/下载：80/0 \| 提交时间：2021/11/05 Bias deep learning encoder-decoder full residual deep network non-linear regression prediction of satellite aerosol optical depth (AOD) and PM2.5 spatiotemporal modeling
	A Novel Model Integrating Deep Learning for Land Use/Cover Change Reconstruction: A Case Study of Zhenlai County, Northeast China 期刊论文 REMOTE SENSING, 2020, 卷号: 12, 期号: 20, 页码: 22 作者: Yubo, Zhang; Zhuoran, Yan; Jiuchun, Yang; Yuanyuan, Yang; Dongyan, Wang 收藏 \| 浏览/下载：9/0 \| 提交时间：2021/03/16 land use change spatiotemporal modeling deep learning model integration
	A Robust Deep Learning Approach for Spatiotemporal Estimation of Satellite AOD and PM2.5 期刊论文 REMOTE SENSING, 2020, 卷号: 12, 期号: 2, 页码: 27 作者: Li, Lianfa 收藏 \| 浏览/下载：16/0 \| 提交时间：2020/05/19 PM2.5 satellite AOD deep learning autoencoder residual network exposure estimation high spatiotemporal resolution
	The Prediction of Finely-Grained Spatiotemporal Relative Human Population Density Distributions in China 期刊论文 IEEE ACCESS, 2020, 卷号: 8, 页码: 181534-181546 作者: Zheng, Zhi; Zhang, Guangyuan 收藏 \| 浏览/下载：8/0 \| 提交时间：2021/03/16 Prediction human population density distribution SARIMA ConvLSTM Tencent positioning data deep learning geographic spatiotemporal big data

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