Results 21 to 30 of about 4,103,347 (253)

Neural Network Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm [PDF]

, 2011
This paper proposes a novel neural network (NN) training method that employs the hybrid exponential smoothing method and the Levenberg–Marquardt (LM) algorithm, which aims to improve the generalization capabilities of previously used methods for training
Jaipal Singh, Chan, Kit Yan, Dillon, Tharam, Singh, Jaipal, Chang, Elizabeth, Elizabeth Chang, Tharam S. Dillon, Kit Yan Chan, Dillon, Tharam S   +8 more
core   +1 more source

Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm

Discrete Dynamics in Nature and Society, 2018
Short-term traffic flow forecasting 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 forecasting remains a challenging task.
Qichun Bing, Dayi Qu, Xiufeng Chen, Fuquan Pan, Jinli Wei   +4 more
doaj   +1 more source

Hybrid Time-Series Forecasting Models for Traffic Flow Prediction [PDF]

, 2022
Traffic flow forecast is critical in today’s transportation system since it is necessary to construct a traffic plan in order to determine a travel route.
Rajalakshmi, V, Ganesh Vaidyanathan, S
core   +1 more source

A Hybrid Forecasting Framework Based on Support Vector Regression with a Modified Genetic Algorithm and a Random Forest for Traffic Flow Prediction

Tsinghua Science and Technology, 2018
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 significant issue due to the complexity and variability of real ...
Lizong Zhang, Nawaf R Alharbe, Guangchun Luo, Zhiyuan Yao, Ying Li   +4 more
doaj   +1 more source

Forecasting of Bicycle and Pedestrian Traffic Using Flexible and Efficient Hybrid Deep Learning Approach

Applied Sciences, 2022
Recently, increasing interest in managing pedestrian and bicycle flows has been demonstrated by cities and transportation professionals aiming to reach community goals related to health, safety, and the environment.
Fouzi Harrou, Abdelkader Dairi, Abdelhafid Zeroual, Ying Sun   +3 more
doaj   +1 more source

MSASGCN :  Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting

Journal of Advanced Transportation, 2022
Traffic flow forecasting is an essential task of an intelligent transportation system (ITS), closely related to intelligent transportation management and resource scheduling.
Yang Cao, Detian Liu, Qizheng Yin, Fei Xue, Hengliang Tang   +4 more
doaj   +1 more source

SSA-ELM: A Hybrid Learning Model for Short-Term Traffic Flow Forecasting

Mathematics
Nowadays, accurate and efficient short-term traffic flow forecasting plays a critical role in intelligent transportation systems (ITS). However, due to the fact that traffic flow is susceptible to factors such as weather and road conditions, traffic flow
Fei Wang, Yinxi Liang, Zhizhe Lin, Jinglin Zhou, Teng Zhou   +4 more
doaj   +1 more source

Short-Term Traffic Flow Forecasting Model Based on GA-TCN

Journal of Advanced Transportation, 2021
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 improved in terms of accuracy and computational efficiency. Therefore,
Rongji Zhang, Feng Sun, Ziwen Song, Xiaolin Wang, Yingcui Du, Shulong Dong   +5 more
doaj   +1 more source

Selection of Significant On−Road Sensor Data for Short−Term Traffic Flow Forecasting Using the Taguchi Method. [PDF]

, 2012
Over the past two decades, neural networks have been applied to develop short-term traffic flow predictors. The past traffic flow data, captured by on-road sensors, is used as input patterns of neural networks to forecast future traffic flow conditions ...
Chan, Kit, Jaipal Singh, T.S. Dillon, V. Palade, J. Singh, Chan, Kit Yan, Palade, Vasile, Elizabeth Chang, S. Khadem, Chan, K.Y., E.Chang, Dillon, Tharam, Khadem, Saghar, Chang, Elizabeth, Saghar Khadem, Dillon, T.S., Tharam S. Dillon, Dillon, Tharam S, Vasile Palade, K.Y. Chan, Palade, V., Singh, Jaipal, Khadem, S., Singh, J., Kit Yan Chan   +24 more
core   +1 more source

A Hybrid Method for Traffic Flow Forecasting Using Multimodal Deep Learning

International Journal of Computational Intelligence Systems, 2020
Traffic flow forecasting has been regarded as a key problem of intelligent transport systems. In this work, we propose a hybrid multimodal deep learning method for short-term traffic flow forecasting, which can jointly and adaptively learn the spatial ...
Shengdong Du, Tianrui Li, Xun Gong, Shi-Jinn Horng   +3 more
doaj   +1 more source