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Chunwei Hu, Xianfeng Liu, Sheng Wu, Fei Yu, Yongkun Song and Jin Zhang
Accurate crowd flow prediction is essential for traffic guidance and traffic control. However, the high nonlinearity, temporal complexity, and spatial complexity that crowd flow data have makes this problem challenging. This research proposes a dynamic g...
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Fan Yin, Chao Li, Haibin Wang, Shihong Zhou, Leixin Nie, Yonglin Zhang and Hao Yin
Digital beamforming techniques find wide applications in the field of underwater acoustic array signal processing. However, their azimuthal resolution has long been constrained by the Rayleigh limit, consequently limiting their detection performance. In ...
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Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li and Fengjun Hu
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
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Zhan Tan, Jiu Ren, Shaoda Li, Wei Li, Rui Zhang and Tiegang Sun
Remote sensing is widely used for lake-water-quality monitoring, but the inversion of the total nitrogen (TN) and total phosphorus (TP) of rivers and non-optical parameters is still a difficult problem. The use of high spatial and temporal resolution mul...
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Hamidreza Marateb, Mina Norouzirad, Kouhyar Tavakolian, Faezeh Aminorroaya, Mohammadreza Mohebbian, Miguel Ángel Mañanas, Sergio Romero Lafuente, Ramin Sami and Marjan Mansourian
Optimal allocation of ward beds is crucial given the respiratory nature of COVID-19, which necessitates urgent hospitalization for certain patients. Several governments have leveraged technology to mitigate the pandemic?s adverse impacts. Based on clinic...
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