Results 31 to 40 of about 11,119,065 (317)

An efficient and intelligent traffic flow prediction method based on LSTM and variational modal decomposition

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
doaj   +1 more source

Short-Term Traffic Flow Prediction Method Based on Spatiotemporal Relativity [PDF]

Jisuanji gongcheng, 2020
The intelligent travel of the new generation intelligent traffic system and the intelligent decision-making of traffic big data need accurate and timely short-term traffic flow prediction.Deep learning can generate features by machine learning technology,
YAN Yang, SUN Lijun, ZHU Lanting
doaj   +1 more source

Prediction model for short‐term traffic flow based on a K‐means‐gated recurrent unit combination

IET Intelligent Transport Systems, 2022
Short‐term forecasting of traffic flow is an indispensable part of easing traffic pressure. Considering that different traffic flow patterns will affect the short‐term traffic flow prediction results, a combined method based on the K‐means clustering ...
Zhaoyun Sun, Yuanjiao Hu, Wei Li, Shaowei Feng, Lili Pei   +4 more
doaj   +1 more source

A novel hybrid deep learning model with ARIMA Conv-LSTM networks and shuffle attention layer for short-term traffic flow prediction

Transportmetrica A: Transport Science, 2023
Traffic flow prediction requires learning of nonlinear spatio-temporal dynamics which becomes challenging due to its inherent nonlinearity and stochasticity.
A. Sattarzadeh, Ronny J. Kutadinata, P. Pathirana, V. Huynh   +3 more
semanticscholar   +1 more source

Improved Equilibrium Optimizer for Short-Term Traffic Flow Prediction

Journal of Database Management, 2023
Meta-heuristic algorithms have been widely used in deep learning. A hybrid algorithm EO-GWO is proposed to train the parameters of long short-term memory (LSTM), which greatly balances the abilities of exploration and exploitation. It utilizes the grey wolf optimizer (GWO) to further search the optimal solutions acquired by equilibrium optimizer (EO ...
Jeng-Shyang Pan 0001, Pei Hu 0001, Tien-Szu Pan, Shu-Chuan Chu 0001   +3 more
openaire   +1 more source

A Short-Term Traffic Flow Reliability Prediction Method considering Traffic Safety [PDF]

Mathematical Problems in Engineering, 2020
With the rapid development and application of intelligent traffic systems, traffic flow prediction has attracted an increasing amount of attention. Accurate and timely traffic flow information is of great significance to improve the safety of transportation. To improve the prediction accuracy of the backward-propagation neural network (BPNN) prediction
Shaoqian Li, Zhenyuan Zhang, Yang Liu, Zixia Qin   +3 more
openaire   +2 more sources

A spatial-temporal short-term traffic flow prediction model based on dynamical-learning graph convolution mechanism [PDF]

Information Sciences, 2022
Short-term traffic flow prediction is a vital branch of the Intelligent Traffic System (ITS) and plays an important role in traffic management. Graph convolution network (GCN) is widely used in traffic prediction models to better deal with the graphical structure
Zhijun Chen, Zheng Lu, Qiushi Chen, Hongliang Zhong, Yishi Zhang, Jie Xue, Chao-Zhong Wu   +6 more
semanticscholar   +1 more source

Traffic pattern prediction in cellular networks. [PDF]

, 2011
PhDIncreasing numbers of users together with a more use of high bit-rate services complicate radio resource management in 3G systems. In order to improve the system capacity and guarantee the QoS, a large amount of research had been carried out on radio ...
Zhang, Kejing
core   +4 more sources

Application of Quantum Genetic Optimization of LVQ Neural Network in Smart City Traffic Network Prediction

IEEE Access, 2020
Accurate prediction of traffic flow in urban networks is of great significance for smart city management. A short-term traffic flow prediction algorithm of Quantum Genetic Algorithm - Learning Vector Quantization (QGA-LVQ) neural network is proposed to ...
Fuquan Zhang, Tsu-Yang Wu, Yiou Wang, Rui Xiong, Gangyi Ding, Peng Mei, Laiyang Liu   +6 more
doaj   +1 more source

Using Upstream and Downstream Traffic Information for Short term Traffic Flow Prediction Based on LSTM Recurrent Neural Network

Journal of Harbin University of Science and Technology, 2019
We employ the long/shortterm memory (LSTM) recurrent neural network to analyze the impact of various input settings on shortterm traffic flow prediction performance First, we compared the shortterm traffic flow prediction performance for different ...
MAN Chun-tao, KANG Dan-qing
doaj   +1 more source