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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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Zheng Zhao, Jialing Yuan and Luhao Chen
Air Traffic Flow Management (ATFM) delay can quantitatively reflect the congestion caused by the imbalance between capacity and demand in an airspace network. Furthermore, it is an important parameter for the ex-post analysis of airspace congestion and t...
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Chang Guo, Jianfeng Zhu and Xiaoming Wang
In recent years, the rapid growth of vehicles has imposed a significant burden on urban road resources. To alleviate urban traffic congestion in intelligent transportation systems (ITS), real-time and accurate traffic flow prediction has emerged as an ef...
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Chang Guo, Demin Li and Xuemin Chen
Analysis of traffic flow signals plays an important role in traffic prediction and management. As an intrinsic property, the singular point of a traffic flow signal labels a new nonsteady status. Therefore, detecting the singular point is an effective ap...
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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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Qingyong Zhang, Lingfeng Zhou, Yixin Su, Huiwen Xia and Bingrong Xu
Considering the spatial and temporal correlation of traffic flow data is essential to improve the accuracy of traffic flow prediction. This paper proposes a traffic flow prediction model named Dual Spatial Convolution Gated Recurrent Unit (DSC-GRU). In p...
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Junwei Zhou, Xizhong Qin, Kun Yu, Zhenhong Jia and Yan Du
Accurate urban traffic flow prediction plays a vital role in Intelligent Transportation System (ITS). The complex long-term and long-range spatiotemporal correlations of traffic flow pose a significant challenge to the prediction task. Most current resea...
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Zhen Yan, Hongyu Yang, Fan Li and Yi Lin
Airport traffic flow prediction is a fundamental research topic in the field of air traffic flow management. Most existing works focus on the single airport traffic flow prediction with temporal dynamics but fail to consider the influence of the topologi...
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Tian Xu and Qingnian Zhang
To analyze the changing characteristics of ship traffic flow in wind farms water area, and to improve the accuracy of ship traffic flow prediction, a Gated Recurrent Unit (GRU) of a Recurrent Neural Network (RNN) was established to analyze multiple traff...
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Xinqiang Chen, Chenxin Wei, Guiliang Zhou, Huafeng Wu, Zhongyu Wang and Salvatore Antonio Biancardo
Automatic Identification System (AIS) data-supported ship trajectory analysis consistently helps maritime regulations and practitioners make reasonable traffic controlling and management decisions. Significant attentions are paid to obtain an accurate sh...
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Mohammed Akallouch, Oussama Akallouch, Khalid Fardousse, Afaf Bouhoute and Ismail Berrada
Accurate and timely traffic information is a vital element in intelligent transportation systems and urban management, which is vitally important for road users and government agencies. However, existing traffic prediction approaches are primarily based ...
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Dangli Wang, Yangran Meng, Shuzhe Chen, Cheng Xie and Zhao Liu
Accurate vessel traffic flow prediction is significant for maritime traffic guidance and control. According to the characteristics of vessel traffic flow data, a new hybrid model, named DWT?Prophet, is proposed based on the discrete wavelet decomposition...
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Xuantong Wang, Jing Li and Tong Zhang
Predicting traffic flow is critical in efficient maritime transportation management, coordination, and planning. Scientists have proposed many prediction methods, most of which are designed for specific locations or for short-term prediction. For the pur...
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S. Gowrishankar,P. S. Satyanarayana
Pág. pp. 53 - 62
The number of users and their network utilization will enumerate the traffic of the network. The accurate and timely estimation of network traffic is increasingly becoming important in achieving guaranteed Quality of Service (QoS) in a wireless network. ...
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Weiqing Zhuang and Yongbo Cao
In the previous research on traffic flow prediction models, most of the models mainly studied the time series of traffic flow, and the spatial correlation of traffic flow was not fully considered. To solve this problem, this paper proposes a method to pr...
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Shuai Lu, Haibo Chen and Yilong Teng
Traffic flow prediction is a crucial research area in traffic management. Accurately predicting traffic flow in each area of the city over the long term can enable city managers to make informed decisions regarding the allocation of urban transportation ...
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Wen Tian, Yining Zhang, Ying Zhang, Haiyan Chen and Weidong Liu
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was co...
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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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Isaac Oyeyemi Olayode, Alessandro Severino, Lagouge Kwanda Tartibu, Fabio Arena and Ziya Cakici
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Vienna N. Katambire, Richard Musabe, Alfred Uwitonze and Didacienne Mukanyiligira
Traffic operation efficiency is greatly impacted by the increase in travel demand and the increase in vehicle ownership. The continued increase in traffic demand has rendered the importance of controlling traffic, especially at intersections. In general,...
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