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Incorporating Multivariate Auxiliary Information for Traffic Prediction on Highways [PDF]
Sensors, 2023 Traffic flow prediction is one of the most important tasks of the Intelligent Transportation Systems (ITSs) for traffic management, and it is also a challenging task affected by many complex factors, such as weather and time.
Bao Li +4 more
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NTAM-LSTM models of network traffic prediction [PDF]
MATEC Web of Conferences, 2022 Accurate prediction of network traffic is very important in allocating network resources. With the rapid development of network technology, network traffic becomes more complex and diverse.
Zhao Jihong, He Xiaoyuan
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Measurement: Sensors, 2023 Traffic flow prediction is a very important research field in intelligent transportation system. The traditional prediction methods have a very wide application in traffic flow prediction.
Jingyi Lu
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IEEE Access, 2021 Traffic prediction helps mitigate the impact of traffic congestion. The accuracy of traffic predictions depends on the availability of the data used for the prediction as well as the prediction model.
Jesus Mena-Oreja, Javier Gozalvez
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UAV-Assisted Traffic Speed Prediction via Gray Relational Analysis and Deep Learning
Drones, 2023 Accurate traffic prediction is crucial to alleviating traffic congestion in cities. Existing physical sensor-based traffic data acquisition methods have high transmission costs, serious traffic information redundancy, and large calculation volumes for ...
Yanliu Zheng +3 more
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Prediction of Traffic Retention Based on TFPCM and Stochastic Model [PDF]
Jisuanji gongcheng, 2019 The prediction of traffic retention is the premise of realizing the automatic timing of intelligent traffic lights.Accurate traffic detention prediction can provide support for the dynamic allocation of traffic signals,thus alleviating urban traffic ...
LI Sha,SUN Lijun
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DeepTSP: Deep traffic state prediction model based on large-scale empirical data
Communications in Transportation Research, 2021 Real-time traffic state (e.g., speed) prediction is an essential component for traffic control and management in an urban road network. How to build an effective large-scale traffic state prediction system is a challenging but highly valuable problem ...
Yang Liu +5 more
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Machine Learning with Variable Sampling Rate for Traffic Prediction in 6G MEC IoT
Discrete Dynamics in Nature and Society, 2022 The high-speed development of mobile broadband networks and IoT applications has brought about massive data transmission and data processing, and severe traffic congestion has adversely affected the fast-growing networks and industries.
Rongqun Peng, Xiuhua Fu, Tian Ding
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Road Traffic Status Prediction Approach Based on Kmeans-Decision Tree Model [PDF]
Journal of Engineering, Project, and Production Management, 2022 An effective way to solve the problem of urban traffic congestion is to predict the road traffic status accurately and take effective traffic control measures in time.
Xinghua Hu, Xinghui Chen, Gao Dai
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Short-term Traffic Flow Prediction Method in Bayesian Networks Based on Quantile Regression
Promet (Zagreb), 2020 With the popularization of intelligent transportation system and Internet of vehicles, the traffic flow data on the urban road network can be more easily obtained in large quantities. This provides data support for shortterm traffic flow prediction based
Jing Luo
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