Results 11 to 20 of about 359,562 (287)

GCN-GAN: Integrating Graph Convolutional Network and Generative Adversarial Network for Traffic Flow Prediction

IEEE Access, 2022
As a necessary component in intelligent transportation systems (ITS), traffic flow-based prediction can accurately estimate the traffic flow in a certain period and area in the future.
Hongling Zheng, Xiang Li, Yongfeng Li, Ziqin Yan, Tinghong Li   +4 more
doaj   +1 more source

AGCN-T: A Traffic Flow Prediction Model for Spatial-Temporal Network Dynamics

Journal of Advanced Transportation, 2022
Traffic prediction is the key for Intelligent Transport Systems (ITS) to achieve traffic control and traffic guidance, and the key challenge is that traffic flow has complex spatial-temporal dependence and nonlinear dynamics.
Jian Feng, Lang Yu, Rui Ma
doaj   +1 more source

STA-GCN: Spatial-Temporal Self-Attention Graph Convolutional Networks for Traffic-Flow Prediction

Applied Sciences, 2023
As an important component of intelligent transportation-management systems, accurate traffic-parameter prediction can help traffic-management departments to conduct effective traffic management.
Zhihong Chang, Chunsheng Liu, Jianmin Jia   +2 more
doaj   +1 more source

A deep network with analogous self‐attention for short‐term traffic flow prediction

IET Intelligent Transport Systems, 2021
Short‐term traffic flow prediction plays a crucial role in research and application of intelligent transportation system. Neural network algorithm can use the big data for training and has more advantages over other prediction models in traffic features ...
Zhao Zhang, Xiaohong Jiao
doaj   +1 more source

Traffic Anomaly Prediction System Using Predictive Network [PDF]

Remote Sensing, 2022
Anomaly anticipation in traffic scenarios is one of the primary challenges in action recognition. It is believed that greater accuracy can be obtained by the use of semantic details and motion information along with the input frames. Most state-of-the art models extract semantic details and pre-defined optical flow from RGB frames and combine them ...
Waqar Riaz, Chenqiang Gao, Abdullah Azeem, null Saifullah, Jamshaid Bux, Asif Ullah   +5 more
openaire   +2 more sources

Long-Term Traffic Scheduling Based on Stacked Bidirectional Recurrent Neural Networks in Inter-Datacenter Optical Networks

IEEE Access, 2019
With the rapid evolution of high-speed mobile communications, cloud computing, and other high-bitrate datacenter-supported services, efficient and flexible traffic scheduling has become one of the fundamental tasks of inter-datacenter optical networks ...
Ao Yu, Hui Yang, Ting Xu, Baoguo Yu, Qiuyan Yao, Yajie Li, Tao Peng, Huifeng Guo, Jun Li, Jie Zhang   +9 more
doaj   +1 more source

Freeway Traffic OscillationsObservations and Predictions [PDF]

, 2002
Freeway traffic was observed over multiple days and was found to display certain regular features. Oscillations arose only in queues; they had periods of several minutes; and their amplitudes stabilized as they propagated upstream. They propagated at a nearly constant speed of about 22 to 24 kilometers per hour, independent of the location within the ...
Mauch, Michael, Cassidy, Michael J.
openaire   +3 more sources

Traffic Status Evolution Trend Prediction Based on Congestion Propagation Effects under Rainy Weather

Journal of Advanced Transportation, 2020
In rainy weather, the accurate prediction of traffic status not only helps road traffic managers to formulate traffic management methods but also helps travelers design travel routes and even adjust travel time.
Yongjie Xue, Rui Feng, Shaohua Cui, Bin Yu   +3 more
doaj   +1 more source

Short-Term Traffic Flow Prediction with Weather Conditions: Based on Deep Learning Algorithms and Data Fusion

Complexity, 2021
Short-term traffic flow prediction is an effective means for intelligent transportation system (ITS) to mitigate traffic congestion. However, traffic flow data with temporal features and periodic characteristics are vulnerable to weather effects, making ...
Yue Hou, Zhiyuan Deng, Hanke Cui
doaj   +1 more source

Truck Traffic Flow Prediction Based on LSTM and GRU Methods With Sampled GPS Data

IEEE Access, 2020
Given the enormous traffic issues, such as congestion and crashes, resulting from the conflicts between trucks and passenger cars, an accurate and reliable prediction of truck traffic flow is needed to enhance the traffic flow efficiency and safety in ...
Shengyou Wang, Jin Zhao, Chunfu Shao, Chunjiao Dong, Chaoying Yin   +4 more
doaj   +1 more source