Survey on traffic prediction in smart cities
The rapid development in machine learning and in the emergence of new data sources
makes it possible to examine and predict traffic conditions in smart cities more accurately …
makes it possible to examine and predict traffic conditions in smart cities more accurately …
A hybrid deep learning model with attention-based conv-LSTM networks for short-term traffic flow prediction
Accurate short-time traffic flow prediction has gained gradually increasing importance for
traffic plan and management with the deployment of intelligent transportation systems (ITSs) …
traffic plan and management with the deployment of intelligent transportation systems (ITSs) …
Short-term traffic flow prediction using seasonal ARIMA model with limited input data
SV Kumar, L Vanajakshi - European Transport Research Review, 2015 - Springer
Background Accurate prediction of traffic flow is an integral component in most of the
Intelligent Transportation Systems (ITS) applications. The data driven approach using Box …
Intelligent Transportation Systems (ITS) applications. The data driven approach using Box …
Deep architecture for traffic flow prediction: Deep belief networks with multitask learning
Traffic flow prediction is a fundamental problem in transportation modeling and
management. Many existing approaches fail to provide favorable results due to being: 1) …
management. Many existing approaches fail to provide favorable results due to being: 1) …
Adaptive multi-kernel SVM with spatial–temporal correlation for short-term traffic flow prediction
X Feng, X Ling, H Zheng, Z Chen… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Accurate estimation of the traffic state can help to address the issue of urban traffic
congestion, providing guiding advices for people's travel and traffic regulation. In this paper …
congestion, providing guiding advices for people's travel and traffic regulation. In this paper …
Short-term traffic forecasting: Where we are and where we're going
EI Vlahogianni, MG Karlaftis, JC Golias - Transportation Research Part C …, 2014 - Elsevier
Since the early 1980s, short-term traffic forecasting has been an integral part of most
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …
Road surface friction prediction using long short-term memory neural network based on historical data
Road surface friction significantly impacts traffic safety and mobility. A precise road surface
friction prediction model can help to alleviate the influence of inclement road conditions on …
friction prediction model can help to alleviate the influence of inclement road conditions on …
Short-term traffic flow forecasting: An experimental comparison of time-series analysis and supervised learning
The literature on short-term traffic flow forecasting has undergone great development
recently. Many works, describing a wide variety of different approaches, which very often …
recently. Many works, describing a wide variety of different approaches, which very often …
Deep learning for edge computing applications: A state-of-the-art survey
With the booming development of Internet-of-Things (IoT) and communication technologies
such as 5G, our future world is envisioned as an interconnected entity where billions of …
such as 5G, our future world is envisioned as an interconnected entity where billions of …
A novel wavelet-SVM short-time passenger flow prediction in Beijing subway system
Y Sun, B Leng, W Guan - Neurocomputing, 2015 - Elsevier
In order to effectively manage the use of existing infrastructures and prevent the emergency
caused by the large gathered crowd, the short-term passenger flow forecasting technology …
caused by the large gathered crowd, the short-term passenger flow forecasting technology …