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References (32)
-
C.S. Zhang, S. Sun, G. Yu (2004)
Proc. IEEE Conf. Intelligent Transportation Systems -
M. Zhong, Satish Sharma, Zhaobin Liu (2005)
Assessing Robustness of Imputation Models Based on Data from Different Jurisdictions: Examples of Alberta and Saskatchewan, CanadaTransportation Research Record, 1917
-
M. Zhong, Satish Sharma, P. Lingras (2004)
Genetically Designed Models for Accurate Imputation of Missing Traffic CountsTransportation Research Record, 1879
-
M. Ahmed, A. Cook (1979)
ANALYSIS OF FREEWAY TRAFFIC TIME-SERIES DATA BY USING BOX-JENKINS TECHNIQUESTransportation Research Record
-
Chenyi Chen, Yin Wang, Li Li, Jianming Hu, Zuo Zhang (2012)
The retrieval of intra-day trend and its influence on traffic predictionTransportation Research Part C-emerging Technologies, 22
-
Li Qu, Jianming Hu, Li Li, Yi Zhang (2009)
PPCA-Based Missing Data Imputation for Traffic Flow Volume: A Systematical ApproachIEEE Transactions on Intelligent Transportation Systems, 10
-
Chao Chen, Jaimyoung Kwon, J. Rice, A. Skabardonis, P. Varaiya (2003)
Detecting Errors and Imputing Missing Data for Single-Loop Surveillance SystemsTransportation Research Record, 1855
-
H. Kim, G.H. Golub, H. Park (2005)
Missing value estimation methods for DNA microarrays gene expression data: local least squares imputation, 21
-
A.P. Dempster, N.M. Laird, D.B. Rubin (1977)
Maximum likelihood from incomplete data via the EM algorithm, 39
-
A. Dempster, N. Laird, D. Rubin (1977)
Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper -
Weihao Yin, Pamela Murray-Tuite, Hesham Rakha (2012)
Imputing Erroneous Data of Single-Station Loop Detectors for Nonincident Conditions: Comparison Between Temporal and Spatial MethodsJournal of Intelligent Transportation Systems, 16
-
Michael Tipping, Charles Bishop (1999)
Mixtures of Probabilistic Principal Component AnalyzersNeural Computation, 11
-
M. Tanner, W. Wong (1987)
The calculation of posterior distributions by data augmentationJournal of the American Statistical Association, 82
-
S. Turner, L. Albert, B. Gajewski, W. Eisele (2000)
Archived Intelligent Transportation System Data Quality: Preliminary Analyses of San Antonio TransGuide DataTransportation Research Record, 1719
-
Zhaobin Liu, Satish Sharma, S. Datla (2008)
Imputation of Missing Traffic Data during Holiday PeriodsTransportation Planning and Technology, 31
-
P. Brockwell, R. Davis (1998)
Introduction to time series and forecasting -
N. Ueda, R. Nakano, Zoubin Ghahramani, Geoffrey Hinton (1998)
Split and Merge EM Algorithm for Improving Gaussian Mixture Density EstimatesJournal of VLSI signal processing systems for signal, image and video technology, 26
-
Bidisha Ghosh, B. Basu, M. O’Mahony (2007)
Bayesian Time-Series Model for Short-Term Traffic Flow ForecastingJournal of Transportation Engineering-asce, 133
-
O. Troyanskaya, M. Cantor, G. Sherlock, P. Brown, T. Hastie, R. Tibshirani, D. Botstein, R. Altman (2001)
Missing value estimation methods for DNA microarraysBioinformatics, 17 6
-
Changshui Zhang, Shiliang Sun, Guoqiang Yu (2004)
A Bayesian network approach to time series forecasting of short-term traffic flowsProceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749)
-
Pavel Sumazin, Gengxin Chen, Naoya Hata, Andrew Smith, Theresa Zhang, Michael Zhang (2005)
DWE: Discriminating Word EnumeratorBioinformatics, 21 1
-
Daiheng Ni, J. Leonard (2005)
Markov Chain Monte Carlo Multiple Imputation Using Bayesian Networks for Incomplete Intelligent Transportation Systems DataTransportation Research Record, 1935
-
Xuexiang Jin, Yi Zhang, D. Yao (2007)
Simultaneously Prediction of Network Traffic Flow Based on PCA-SVR -
H. Dia (2001)
An object-oriented neural network approach to short-term traffic forecastingEur. J. Oper. Res., 131
-
G. McLachlan, T. Krishnan (1996)
The EM algorithm and extensions -
Sangsoo Lee, D. Fambro (1999)
Application of Subset Autoregressive Integrated Moving Average Model for Short-Term Freeway Traffic Volume ForecastingTransportation Research Record, 1678
-
Manoel Castro-Neto, Young-Seon Jeong, M. Jeong, Lee Han (2009)
Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditionsExpert Syst. Appl., 36
-
P. Green (1996)
Markov chain Monte Carlo in Practice -
M. Dougherty (1995)
A REVIEW OF NEURAL NETWORKS APPLIED TO TRANSPORTTransportation Research Part C-emerging Technologies, 3
-
E. Vlahogianni, M. Karlaftis, J. Golias (2005)
Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approachTransportation Research Part C-emerging Technologies, 13
-
K. Pearson
III. Contributions to the mathematical theory of evolutionProceedings of the Royal Society of London, 54
-
S. Lee, D. Fambro (1999)
Application of the subset ARIMA model for short?term freeway traffic volume forecasting, 1678
- Publisher
- Wiley
- Copyright
- © 2020 The Institution of Engineering and Technology
- eISSN
- 1751-9578
- DOI
- 10.1049/iet-its.2013.0052
- Publisher site
- See Article on Publisher Site
Abstract
Journal
IET Intelligent Transport Systems – Wiley
Published: Feb 1, 2014
Keywords: ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;