EnLSTM-WPEO: Short-term traffic flow prediction by ensemble LSTM, NNCT weight integration, and population extremal optimization
Accurate and stable short-term traffic flow prediction is an indispensable part in current
intelligent transportation systems. In this paper, a novel short-term traffic flow forecasting …
intelligent transportation systems. In this paper, a novel short-term traffic flow forecasting …
Traffic volume forecasting based on radial basis function neural network with the consideration of traffic flows at the adjacent intersections
The forecasting of short-term traffic flow is one of the key issues in the field of dynamic traffic
control and management. Because of the uncertainty and nonlinearity, short-term traffic flow …
control and management. Because of the uncertainty and nonlinearity, short-term traffic flow …
Urban rail transit passenger flow forecast based on LSTM with enhanced long‐term features
D Yang, K Chen, M Yang, X Zhao - IET Intelligent Transport …, 2019 - Wiley Online Library
Outbreak passenger flow is the main cause of rail transit congestion. In this regard, the
accurate forecast of passenger flow in advance will facilitate the traffic control department to …
accurate forecast of passenger flow in advance will facilitate the traffic control department to …
Simultaneously prediction of network traffic flow based on PCA-SVR
X Jin, Y Zhang, D Yao - International Symposium on Neural Networks, 2007 - Springer
The ability to predict traffic variables such as speed, travel time and flow, based on real time
and historic data, collected by various systems in transportation networks, is vital to the …
and historic data, collected by various systems in transportation networks, is vital to the …
Traffic flow prediction with long short-term memory networks (LSTMs)
H Shao, BH Soong - 2016 IEEE region 10 conference …, 2016 - ieeexplore.ieee.org
Accurate traffic flow information is crucial for an intelligent transportation system
management and deployment. Over the past few years, many existing models have been …
management and deployment. Over the past few years, many existing models have been …
Traffic flow prediction model based on deep belief network and genetic algorithm
Y Zhang, G Huang - IET Intelligent Transport Systems, 2018 - Wiley Online Library
Traffic flow prediction plays an indispensable role in the intelligent transportation system.
The effectiveness of traffic control and management relies heavily on the prediction …
The effectiveness of traffic control and management relies heavily on the prediction …
Daily traffic flow forecasting through a contextual convolutional recurrent neural network modeling inter-and intra-day traffic patterns
Traffic flow forecasting is an important problem for the successful deployment of intelligent
transportation systems, which has been studied for more than two decades. In recent years …
transportation systems, which has been studied for more than two decades. In recent years …
ANN based short-term traffic flow forecasting in undivided two lane highway
Short term traffic forecasting is one of the important fields of study in the transportation
domain. Short term traffic forecasting is very useful to develop a more advanced …
domain. Short term traffic forecasting is very useful to develop a more advanced …
A hybrid deep learning based traffic flow prediction method and its understanding
Deep neural networks (DNNs) have recently demonstrated the capability to predict traffic
flow with big data. While existing DNN models can provide better performance than shallow …
flow with big data. While existing DNN models can provide better performance than shallow …
A hybrid deep learning framework for long-term traffic flow prediction
Y Li, S Chai, Z Ma, G Wang - IEEE Access, 2021 - ieeexplore.ieee.org
An accurate and reliable traffic flow prediction is of great significance, especially the long-
term traffic flow prediction eg, 24 hours, which can help the traffic decision-makers formulate …
term traffic flow prediction eg, 24 hours, which can help the traffic decision-makers formulate …