A Unified STARIMA based Model for Short-term Traffic Flow Prediction
暂无分享,去创建一个
Guoqiang Mao | Wenwei Yue | Peibo Duan | Shangbo Wang | Guoqiang Mao | Shangbo Wang | Peibo Duan | Wenwei Yue
[1] Se-do Oh,et al. Urban Traffic Flow Prediction System Using a Multifactor Pattern Recognition Model , 2015, IEEE Transactions on Intelligent Transportation Systems.
[2] Wanli Min,et al. Real-time road traffic prediction with spatio-temporal correlations , 2011 .
[3] Guoqiang Mao,et al. STARIMA-based traffic prediction with time-varying lags , 2016, 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC).
[4] Kian Hsiang Low,et al. Gaussian Process Decentralized Data Fusion and Active Sensing for Spatiotemporal Traffic Modeling and Prediction in Mobility-on-Demand Systems , 2015, IEEE Transactions on Automation Science and Engineering.
[5] Dimitrios Tzovaras,et al. Managing Spatial Graph Dependencies in Large Volumes of Traffic Data for Travel-Time Prediction , 2016, IEEE Transactions on Intelligent Transportation Systems.
[6] Jinyoung Ahn,et al. Highway traffic flow prediction using support vector regression and Bayesian classifier , 2016, 2016 International Conference on Big Data and Smart Computing (BigComp).
[7] Chang-Tien Lu,et al. Traffic Flow Prediction for Urban Network using Spatio-Temporal Random , 2011 .
[8] Jiaqiu Wang,et al. A Dynamic Spatial Weight Matrix and Localized Space–Time Autoregressive Integrated Moving Average for Network Modeling , 2014 .
[9] Ruimin Li,et al. Evaluation of speed-based travel time estimation models , 2006 .
[10] Dave Hale. An efficient method for computing local cross-correlations of multi-dimensional signals , 2006 .
[11] Rajesh Krishnan,et al. On the estimation of space-mean-speed from inductive loop detector data , 2010 .
[12] Yinhai Wang,et al. Improving Dual-Loop Truck (and Speed) Data: Quick Detection of Malfunctioning Loops and Calculation of Required Adjustments , 2006 .
[13] Li Li,et al. Missing traffic data: comparison of imputation methods , 2014 .