JKSCE
KSCE JOURNAL OF CIVIL AND
ENVIRONMENTAL ENGINEERING RESEARCH
KSCE
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ISSN : 1015-6348 (Print)
ISSN : 2799-9629 (Online)
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Journal of the Korean Society of Civil Engineers
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KSCE J. Civ. Environ. Eng. Res.
Open Access, Bi-monthly
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2018-08
(v.38 n.4)
10.12652/Ksce.2018.38.4.0579
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REF
1
Asif, M. T., Dauwels, J., Goh, C. Y., Oran, A., Fathi, E., Xu, M. and Jaillet, P. (2014). “Spatiotemporal patterns in large-scale traffic speed prediction.” IEEE Transactions on Intelligent Transportation Systems, Vol. 15, No. 2, pp. 794-804.
2
Chang, H. and Yoon, B. (2018). “Multiple period forecasting of motorway traffic volumes by using big historical data.” Journal of the Korean Society of Civil Engineers, Vol. 38, No. 1, pp. 73-80 (in Korean).
3
Fusco, G., Colombaroni, C. and Isaenko, N. (2016). “Short-term speed predictions exploiting big data on large urban road networks.” Transportation Research Part C: Emerging Technologies, Vol. 73, pp. 183-201.
4
Hamad, K., Shourijeh, M. T., Lee, E. and Faghri, A. (2009). “Near-term travel speed prediction utilizing Hilbert-Huang transform.” Computer- Aided Civil and Infrastructure Engineering, Vol. 24, No. 8, pp. 551-576.
5
Jiang, X., Zhang, L. and Chen, M. X. (2014). “Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China.” Transportation Research Part C: Emerging Technologies, Vol. 44, pp. 110-127.
6
Kim, H. and Jang, K. (2013). “Short-term prediction of travle time using DSRC on highway.” Journal of the Korean Society of Civil Engineers, Vol. 33, No. 6, pp. 2465-2471 (in Korean).
7
Luukko, P. J. J., Helske, J. and Räsänen, E. (2016). “Introducing libeemd: A program package for performing the ensemble empirical mode decomposition.” Computational Statistics, Vol. 31, No. 2, pp. 545-557.
8
Myung, J., Kim, D. K., Kho, S. Y. and Park, C. H. (2012). “Travel time prediction using k nearest neighbor method with combined data from vehicle detector system and automatic toll collection system.” Transportation Research Record: Journal of the Transportation Research Board, Vol. 2011, pp. 51-59.
9
Oh, C. and Park, S. (2011). “Investigating the effects of daily travel time patterns on short-term prediction.” KSCE Journal of Civil Engineering, Vol. 15, No. 7, pp. 1263-1272.
10
Shin, K., Shim, S., Choi, K. and Kim, S. (2014). “Expressway travel time prediction using k-nearest neighborhood.” Journal of the Korean Society of Civil Engineers, Vol. 34, No. 6, pp. 1873-1879 (in Korean).
11
Vlahogianni, E. I., Karlaftis, M. G. and Golias, J. C. (2014). “Short-term traffic forecasting: Where we are and where we’re going.” Transportation Research Part C: Emerging Technologies, Vol. 43, pp. 3-19.
12
Wang, H., Liu, L., Qian, Z., Wei, H. and Dong, S. (2014). “Empirical mode decomposition–autoregressive integrated moving average: Hybrid short-term traffic speed prediction model.” Transportation Research Record: Journal of the Transportation Research Board, Vol. 2460, pp. 66-76.
13
Wei, Y. and Chen, M. C. (2012). “Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks.” Transportation Research Part C: Emerging Technologies, Vol. 21, pp. 148-162.
14
Wu, Z. H. and Huang, N. E. (2009). “Ensemble empirical mode decomposition: A noise assisted data analysis method.” Advances in Adaptive Data Analysis, Vol. 1, No. 1, pp. 1-41.