A short-term traffic flow prediction model based on an improved gate recurrent unit neural network

W Shu, K Cai, NN Xiong - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
With the increasing demand for intelligent transportation systems, short-term traffic flow
prediction has become an important research direction. The memory unit of a Long Short …

[HTML][HTML] A combined method for short-term traffic flow prediction based on recurrent neural network

S Lu, Q Zhang, G Chen, D Seng - Alexandria Engineering Journal, 2021 - Elsevier
The accurate prediction of real-time traffic flow is indispensable to intelligent transport
systems. However, the short-term prediction remains a thorny issue, due to the complexity …

Predicting short-term traffic flow by long short-term memory recurrent neural network

Y Tian, L Pan - 2015 IEEE international conference on smart …, 2015 - ieeexplore.ieee.org
Intelligent Transportation System (ITS) is a significant part of smart city, and short-term traffic
flow prediction plays an important role in intelligent transportation management and route …

Hybrid LSTM neural network for short-term traffic flow prediction

Y Xiao, Y Yin - Information, 2019 - mdpi.com
The existing short-term traffic flow prediction models fail to provide precise prediction results
and consider the impact of different traffic conditions on the prediction results in an actual …

Short-term traffic flow prediction for urban road sections based on time series analysis and LSTM_BILSTM method

C Ma, G Dai, J Zhou - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
The real-time performance and accuracy of traffic flow prediction directly affect the efficiency
of traffic flow guidance systems, and traffic flow prediction is a hotspot in the field of …

Short-term traffic flow prediction with LSTM recurrent neural network

D Kang, Y Lv, Y Chen - 2017 IEEE 20th international …, 2017 - ieeexplore.ieee.org
Accurate and timely short-term traffic flow prediction plays an important role in intelligent
transportation management and control. Traffic flow prediction has a long history and is still …

Data-driven short-term forecasting for urban road network traffic based on data processing and LSTM-RNN

W Xiangxue, X Lunhui, C Kaixun - Arabian Journal for Science and …, 2019 - Springer
A short-term traffic flow prediction framework is proposed for urban road networks based on
data-driven methods that mainly include two modules. The first module contains a set of …

T-LSTM: A long short-term memory neural network enhanced by temporal information for traffic flow prediction

L Mou, P Zhao, H Xie, Y Chen - Ieee Access, 2019 - ieeexplore.ieee.org
Short-term traffic flow prediction is one of the most important issues in the field of intelligent
transportation systems. It plays an important role in traffic information service and traffic …

Short-term traffic flow prediction using the modified elman recurrent neural network optimized through a genetic algorithm

A Sadeghi-Niaraki, P Mirshafiei, M Shakeri… - IEEE …, 2020 - ieeexplore.ieee.org
Traffic stream determining is an essential part of the intelligent transportation management
system. Precise prediction of traffic flow provides a basis for other tasks, like forecasting …

Using LSTM and GRU neural network methods for traffic flow prediction

R Fu, Z Zhang, L Li - 2016 31st Youth academic annual …, 2016 - ieeexplore.ieee.org
Accurate and real-time traffic flow prediction is important in Intelligent Transportation System
(ITS), especially for traffic control. Existing models such as ARMA, ARIMA are mainly linear …