A Match‐Then‐Predict Method for Daily Traffic Flow Forecasting Based on Group Method of Data Handling
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Xiang Song | Yinhai Wang | Wenjing Li | Dianhai Wang | Dongfang Ma | Licheng Qu | Yinhai Wang | Dianhai Wang | Dongfang Ma | X. Song | Wenjing Li | L. Qu
[1] Hojjat Adeli,et al. Dynamic Wavelet Neural Network Model for Traffic Flow Forecasting , 2005 .
[2] Xiaolei Ma,et al. DRIVE Net , 2011 .
[3] Chao Chen,et al. Short‐Term Traffic Speed Prediction for an Urban Corridor , 2017, Comput. Aided Civ. Infrastructure Eng..
[4] Eligius M. T. Hendrix,et al. Traffic Responsive Control of Intersections with Predicted Arrival Times: A Markovian Approach , 2014, Comput. Aided Civ. Infrastructure Eng..
[5] A.J.R. Reis,et al. NeuroDem-a neural network based short term demand forecaster , 2001, 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502).
[6] Stephen D. Boyles,et al. Demand Profiling for Dynamic Traffic Assignment by Integrating Departure Time Choice and Trip Distribution , 2016, Comput. Aided Civ. Infrastructure Eng..
[7] Michael Schreckenberg,et al. Effect of driver over-acceleration on traffic breakdown in three-phase cellular automaton traffic flow models , 2013 .
[8] R. E. Abdel-Aal,et al. Modeling and forecasting the mean hourly wind speed time series using GMDH-based abductive networks , 2009 .
[9] Amir Hossein Gandomi,et al. A computational intelligence‐based approach for short‐term traffic flow prediction , 2010, Expert Syst. J. Knowl. Eng..
[10] Man-Chun Tan,et al. An Aggregation Approach to Short-Term Traffic Flow Prediction , 2009, IEEE Transactions on Intelligent Transportation Systems.
[11] Michael Patriksson,et al. A Mixed User‐Equilibrium and System‐Optimal Traffic Flow for Connected Vehicles Stated as a Complementarity Problem , 2017, Comput. Aided Civ. Infrastructure Eng..
[12] Anne M. Denton,et al. Density-based Clustering of Time Series Subsequences , 2004 .
[13] Fei-Yue Wang,et al. Traffic Flow Prediction With Big Data: A Deep Learning Approach , 2015, IEEE Transactions on Intelligent Transportation Systems.
[14] Paolo Frasconi,et al. Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning , 2013, IEEE Transactions on Intelligent Transportation Systems.
[15] Hojjat Adeli,et al. Wavelet Packet‐Autocorrelation Function Method for Traffic Flow Pattern Analysis , 2004 .
[16] Jin Wang,et al. Short-term traffic speed forecasting hybrid model based on Chaos–Wavelet Analysis-Support Vector Machine theory , 2013 .
[17] Martin Treiber,et al. Validation of traffic flow models with respect to the spatiotemporal evolution of congested traffic patterns , 2012 .
[18] L. Vanajakshi,et al. A comparison of the performance of artificial neural networks and support vector machines for the prediction of traffic speed , 2004, IEEE Intelligent Vehicles Symposium, 2004.
[19] Babak Nadjar Araabi,et al. Traffic Flow Prediction Using MI Algorithm and Considering Noisy and Data Loss Conditions: An Application to Minnesota Traffic Flow Prediction , 2014 .
[20] Mei Chen,et al. A Nested Clustering Technique for Freeway Operating Condition Classification , 2007, Comput. Aided Civ. Infrastructure Eng..
[21] Matthew G. Karlaftis,et al. A multivariate state space approach for urban traffic flow modeling and prediction , 2003 .
[22] Eleni I. Vlahogianni,et al. Temporal Evolution of Short‐Term Urban Traffic Flow: A Nonlinear Dynamics Approach , 2008, Comput. Aided Civ. Infrastructure Eng..
[23] Eamonn J. Keogh,et al. Clustering of time-series subsequences is meaningless: implications for previous and future research , 2004, Knowledge and Information Systems.
[24] Hilmi Berk Celikoglu,et al. An Approach to Dynamic Classification of Traffic Flow Patterns , 2013, Comput. Aided Civ. Infrastructure Eng..
[25] Mecit Cetin,et al. Short-Term Traffic Flow Prediction with Regime Switching Models , 2006 .
[26] Adel W. Sadek,et al. A k Nearest Neighbor based Local Linear Wavelet Neural Network Model for On-line Short-term Traffic Volume Prediction , 2013 .
[27] Der-Horng Lee,et al. Short-term freeway traffic flow prediction : Bayesian combined neural network approach , 2006 .
[28] Alessandro Laio,et al. Clustering by fast search and find of density peaks , 2014, Science.
[29] Moshe Ben-Akiva,et al. Personalized Menu Optimization with Preference Updater: A Boston Case Study , 2018 .
[30] Zhirui Ye,et al. Short‐Term Traffic Volume Forecasting Using Kalman Filter with Discrete Wavelet Decomposition , 2007, Comput. Aided Civ. Infrastructure Eng..
[31] Eleni I. Vlahogianni,et al. Short‐term traffic forecasting: Overview of objectives and methods , 2004 .
[32] Eleni I. Vlahogianni,et al. Short-term traffic forecasting: Where we are and where we’re going , 2014 .
[33] Hojjat Adeli,et al. Neural network model for rapid forecasting of freeway link travel time , 2003 .
[34] Moshe Ben-Akiva,et al. The concept and impact analysis of a flexible mobility on demand system , 2015 .
[35] Kyoung-jae Kim,et al. Financial time series forecasting using support vector machines , 2003, Neurocomputing.
[36] Wei Huang,et al. A clustering approach to online freeway traffic state identification using ITS data , 2010 .
[37] Geert Wets,et al. Investigating the Variability in Daily Traffic Counts through use of ARIMAX and SARIMAX Models , 2009 .
[38] Mecit Cetin,et al. Short-term traffic flow rate forecasting based on identifying similar traffic patterns , 2016 .
[39] Gurcan Comert,et al. An Online Change-Point-Based Model for Traffic Parameter Prediction , 2013, IEEE Transactions on Intelligent Transportation Systems.
[40] Qiuchen Liu,et al. An Improved K-nearest Neighbor Model for Short-term Traffic Flow Prediction , 2013 .
[41] Eleni I. Vlahogianni,et al. Spatio‐Temporal Short‐Term Urban Traffic Volume Forecasting Using Genetically Optimized Modular Networks , 2007, Comput. Aided Civ. Infrastructure Eng..
[42] Fan Li,et al. Model-based monitoring and fault diagnosis of fossil power plant process units using Group Method of Data Handling. , 2009, ISA transactions.
[43] Serge P. Hoogendoorn,et al. Real-Time Lagrangian Traffic State Estimator for Freeways , 2012, IEEE Transactions on Intelligent Transportation Systems.
[44] Hojjat Adeli,et al. Mesoscopic-Wavelet Freeway Work Zone Flow and Congestion Feature Extraction Model , 2004 .
[45] Francisco Javier Díaz Pernas,et al. Wavelet‐Based Denoising for Traffic Volume Time Series Forecasting with Self‐Organizing Neural Networks , 2010, Comput. Aided Civ. Infrastructure Eng..
[46] Yin Wang,et al. The retrieval of intra-day trend and its influence on traffic prediction , 2012 .
[47] Yupo Chan,et al. A microstate spatial-inference model for network-traffic estimation , 2013 .
[48] Yunlong Zhang,et al. Forecasting of Short-Term Freeway Volume with v-Support Vector Machines , 2007 .
[49] C. L. Philip Chen,et al. Data-intensive applications, challenges, techniques and technologies: A survey on Big Data , 2014, Inf. Sci..
[50] Mei Chen,et al. Defining Traffic Flow Phases Using Intelligent Transportation Systems-Generated Data , 2007, J. Intell. Transp. Syst..
[51] W. Weijermars,et al. Analyzing highway flow patterns using cluster analysis , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..
[52] Li Li,et al. Using LSTM and GRU neural network methods for traffic flow prediction , 2016, 2016 31st Youth Academic Annual Conference of Chinese Association of Automation (YAC).
[53] Billy M. Williams,et al. Comparison of parametric and nonparametric models for traffic flow forecasting , 2002 .
[54] Markos Papageorgiou,et al. Real-time freeway traffic state estimation based on extended Kalman filter: a general approach , 2005 .
[55] Biswajit Basu,et al. Random Process Model for Urban Traffic Flow Using a Wavelet‐Bayesian Hierarchical Technique , 2010, Comput. Aided Civ. Infrastructure Eng..
[56] Fei-Yue Wang,et al. Data-Driven Intelligent Transportation Systems: A Survey , 2011, IEEE Transactions on Intelligent Transportation Systems.
[57] S. Mehdi Hashemi,et al. Modeling and Forecasting the Urban Volume Using Stochastic Differential Equations , 2014, IEEE Transactions on Intelligent Transportation Systems.
[58] Hannes Koller,et al. Predicting Motorway Traffic Performance by Data Fusion of Local Sensor Data and Electronic Toll Collection Data , 2011, Comput. Aided Civ. Infrastructure Eng..
[59] Ricardo García-Ródenas,et al. An Approach to Dynamical Classification of Daily Traffic Patterns , 2017, Comput. Aided Civ. Infrastructure Eng..
[60] Zhiming Cui,et al. Fuzzy c-means clustering and opposition-based reinforcement learning for traffic congestion identification , 2012 .
[61] Antony Stathopoulos,et al. Fuzzy Modeling Approach for Combined Forecasting of Urban Traffic Flow , 2008, Comput. Aided Civ. Infrastructure Eng..
[62] Hojjat Adeli,et al. Neural Networks in Civil Engineering: 1989–2000 , 2001 .
[63] Lee D. Han,et al. Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions , 2009, Expert Syst. Appl..