Feature selection and extraction in spatiotemporal traffic forecasting: a systematic literature review
Author:
Funder
European Regional Development Fund
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Transportation,Automotive Engineering
Link
http://link.springer.com/content/pdf/10.1186/s12544-019-0345-9.pdf
Reference93 articles.
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2. Vlahogianni, E. I., Karlaftis, M. G., & Golias, J. C. (2014). Short-term traffic forecasting: Where we are and where we’re going. Transportation Research Part C: Emerging Technologies, 43, 3–19 https://doi.org/10.1016/j.trc.2014.01.005 .
3. Haworth, J. (2014). Spatio-temporal forecasting of network data. London: PhD diss., University College London.
4. Ermagun, A., & Levinson, D. (2018). Spatiotemporal traffic forecasting: Review and proposed directions. Transport Reviews, 1–29. https://doi.org/10.1080/01441647.2018.1442887 .
5. George, B., & Kim, S. (2013). Spatio-temporal networks. New York: Springer New York.
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