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Zhe Zheng, Bo Zou, Wenbin Wei and Wen Tian
The ability to accurately predict flight time of arrival in real time during a flight is critical to the efficiency and reliability of aviation system operations. This paper proposes a data-light and trajectory-based machine learning approach for the onl...
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Zhuoming Du, Junfeng Zhang and Bo Kang
Decision support tools for arrival sequencing and scheduling could assist air traffic controllers in managing the arrival aircraft in terminal areas. However, one critical issue is that the current method for dealing with the arrival sequencing and sched...
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Jianwei Geng, Hengpeng Li, Wenfei Luan, Yunjie Shi, Jiaping Pang and Wangshou Zhang
The tea plant (Camellia sinensis), as a major, global cash crop providing beverages, is facing major challenges from droughts and water shortages due to climate change. The accurate estimation of the actual evapotranspiration (ETa) of tea plants is essen...
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Thilo Reich, David Hulbert and Marcin Budka
This study presents a working concept of a model architecture allowing to leverage the state of an entire transport network to make estimated arrival time (ETA) and next-step location predictions. To this end, a combination of an attention mechanism with...
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Jeong-Hyun Yoon, Dong-Ham Kim, Sang-Woong Yun, Hye-Jin Kim and Sewon Kim
Container terminals are at the center of global logistics, and are highly dependent on the schedule of vessels arriving. Conventional ETA records from ships, utilized for terminal berth planning, lack sufficient accuracy for effective plan implementation...
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Ammar Rafiei Emam, Martin Kappas, Nguyen Hoang Khanh Linh and Tsolmon Renchin
The A-Luoi district in Thua Thien Hue province of Vietnam is under extreme pressure from natural and anthropogenic factors. The area is ungauged and suffering from data scarcity. To evaluate the water resources availability and water management, we used ...
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