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Xianlei Fu, Maozhi Wu, Sasthikapreeya Ponnarasu and Limao Zhang
This research introduces a hybrid deep learning approach to perform real-time forecasting of passenger traffic flow for the metro railway system (MRS). By integrating long short-term memory (LSTM) and the graph convolutional network (GCN), a hybrid deep ...
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Petros Brimos, Areti Karamanou, Evangelos Kalampokis and Konstantinos Tarabanis
Traffic forecasting has been an important area of research for several decades, with significant implications for urban traffic planning, management, and control. In recent years, deep-learning models, such as graph neural networks (GNN), have shown grea...
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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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Zhihong Chang, Chunsheng Liu and Jianmin Jia
As an important component of intelligent transportation-management systems, accurate traffic-parameter prediction can help traffic-management departments to conduct effective traffic management. Due to the nonlinearity, complexity, and dynamism of highwa...
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Amr Bahaa, Mohamed Shehata, Safa M. Gasser and Mohamed S. El-Mahallawy
An explosion of traffic volume is the main driver behind launching various 5G services. The 5G network will utilize the IP Multimedia Subsystems (IMS) as a core network, same as in 4G networks. Thus, ensuring a high level of survivability and efficient f...
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Dong Sui, Kechen Liu and Qian Li
Air traffic situation prediction is critical for traffic flow management and the optimal allocation of airspace resources. In this study, the multi-sector airspace scenario is abstracted into an undirected graph. A spatiotemporal graph convolutional netw...
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Zhiyang Sun, Tiancheng Guo, Shiyu Luo, Yingqiu Zhuang, Yuke Ma, Yang Chen and Xin Wang
Understanding the network usage patterns of university users is very important today. This paper focuses on the research of DNS request behaviors of university users in Shanghai, China. Based on the DNS logs of a large number of university users recorded...
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Guto Leoni Santos, Patricia Takako Endo, Djamel Sadok and Judith Kelner
This last decade, the amount of data exchanged on the Internet increased by over a staggering factor of 100, and is expected to exceed well over the 500 exabytes by 2020. This phenomenon is mainly due to the evolution of high-speed broadband Internet and...
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The freight forecasting of river-sea direct transport (RSDT) is crucial for the policy making of river-sea transportation facilities and the decision-making of relevant port and shipping companies. This paper develops a multi-step approach framework for ...
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Robert Truong, Olga Gkountouna, Dieter Pfoser and Andreas Züfle
The problem of traffic prediction is paramount in a plethora of applications, ranging from individual trip planning to urban planning. Existing work mainly focuses on traffic prediction on road networks. Yet, public transportation contributes a significa...
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