Support vector machine for short-term traffic flow prediction and improvement of its model training using nearest neighbor approach
Short-term prediction of traffic flow is essential for the deployment of intelligent transportation
systems. In this paper we present an efficient method for short-term traffic flow prediction …
systems. In this paper we present an efficient method for short-term traffic flow prediction …
An evaluation of HTM and LSTM for short-term arterial traffic flow prediction
Recent years have seen the emergence of two significant technologies: big data systems
capable of storing, retrieving, and processing large amounts of data, and machine learning …
capable of storing, retrieving, and processing large amounts of data, and machine learning …
[HTML][HTML] A real-time network-level traffic signal control methodology with partial connected vehicle information
This paper presents two algorithms to estimate traffic state in urban street networks with a
mixed traffic stream of connected and unconnected vehicles and incorporates them in a real …
mixed traffic stream of connected and unconnected vehicles and incorporates them in a real …
[HTML][HTML] An autoencoder and LSTM-based traffic flow prediction method
Smart cities can effectively improve the quality of urban life. Intelligent Transportation System
(ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow …
(ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow …
Short‐term traffic flow forecasting model based on GA‐TCN
R Zhang, F Sun, Z Song, X Wang… - Journal of Advanced …, 2021 - Wiley Online Library
Traffic flow forecasting is the key to an intelligent transportation system (ITS). Currently, the
short‐term traffic flow forecasting methods based on deep learning need to be further …
short‐term traffic flow forecasting methods based on deep learning need to be further …
Traffic signal optimization for partially observable traffic system and low penetration rate of connected vehicles
Observability and controllability are two critical requirements for a partially observable
transportation system. This paper proposes a stepwise signal optimization framework with …
transportation system. This paper proposes a stepwise signal optimization framework with …
Hybrid statistical and machine learning methods for road traffic prediction: A review and tutorial
B Alsolami, R Mehmood, A Albeshri - Smart Infrastructure and Applications …, 2020 - Springer
Mobility is one of the major dimensions of smart city design and development.
Transportation analysis and prediction play important parts in mobility research and …
Transportation analysis and prediction play important parts in mobility research and …
Short-term traffic flow prediction based on least square support vector machine with hybrid optimization algorithm
Accurate short-term traffic flow prediction plays an indispensable role for solving traffic
congestion. However, the structure of traffic data is nonlinear and complicated. It is a …
congestion. However, the structure of traffic data is nonlinear and complicated. It is a …
Lagrangian sensing: traffic estimation with mobile devices
DB Work, OP Tossavainen, Q Jacobson… - 2009 American …, 2009 - ieeexplore.ieee.org
An inverse modeling algorithm is developed to reconstruct the state of traffic (velocity field)
on highways from GPS measurements gathered from mobile phones traveling on-board …
on highways from GPS measurements gathered from mobile phones traveling on-board …
A hybrid forecasting framework based on support vector regression with a modified genetic algorithm and a random forest for traffic flow prediction
L Zhang, NR Alharbe, G Luo, Z Yao… - Tsinghua Science and …, 2018 - ieeexplore.ieee.org
The ability to perform short-term traffic flow forecasting is a crucial component of intelligent
transportation systems. However, accurate and reliable traffic flow forecasting is still a …
transportation systems. However, accurate and reliable traffic flow forecasting is still a …