Altman, N. S. (1992). “An introduction to kernel and nearest- neighbor nonparametric regression.” The American Statistician, Vol. 46, pp. 175-185. Altman, N. S. (1992). “An introduction to kernel and nearest- neighbor nonparametric regression.” The American Statistician, Vol. 46, pp. 175-185.

Chang, H. and Lee, S. (2003). “A study on link travel time prediction by short term simulation based on CA.” Journal of Korean Society of Transportation, Vol. 21, No. 1, pp. 91-102 (in Korean).Chang, H. and Lee, S. (2003). “A study on link travel time prediction by short term simulation based on CA.” Journal of Korean Society of Transportation, Vol. 21, No. 1, pp. 91-102 (in Korean).

Chang, H., Park, D., Lee, S., Lee, H. and Baek, S. “Dynamic multi-interval bus travel time prediction using bus transit data.” Transportmetrica, Vol. 6, No. 1, pp. 19-38.10.1080/18128600902929591Chang, H., Park, D., Lee, S., Lee, H. and Baek, S. “Dynamic multi-interval bus travel time prediction using bus transit data.” Transportmetrica, Vol. 6, No. 1, pp. 19-38.

Davis, G. and Nihan, N. (1991). “Nonparametric regression and short-term freeway traffic forecasting.” Journal of Transportation Engineering, Vol. 117, No. 2, pp. 178-188.10.1061/(ASCE)0733-947X(1991)117:2(178)Davis, G. and Nihan, N. (1991). “Nonparametric regression and short-term freeway traffic forecasting.” Journal of Transportation Engineering, Vol. 117, No. 2, pp. 178-188.

Karlsson, M. and Yakowitz, S. (1987). “Rainfall-runoff forecasting methods, old and new.” Stochastic Hydrology and Hydraulics, Vol. 1, No. 4, pp. 303-318.10.1007/BF01543102Karlsson, M. and Yakowitz, S. (1987). “Rainfall-runoff forecasting methods, old and new.” Stochastic Hydrology and Hydraulics, Vol. 1, No. 4, pp. 303-318.

Mulhern, F. J. and Caprara, R. J. (1994). “A nearest neighbor model for forecasting market response.” International Journal of Forecasting, Vol. 10, No. 2, pp. 191-207.10.1016/0169-2070(94)90002-7Mulhern, F. J. and Caprara, R. J. (1994). “A nearest neighbor model for forecasting market response.” International Journal of Forecasting, Vol. 10, No. 2, pp. 191-207.

Oswald, R. K., Scherer, W. T. and Smith, B. (2000). “Traffic flow forecasting using approximate nearest neighbor nonparametric regression.” A research project report for U.S. DOT University transportation center.Oswald, R. K., Scherer, W. T. and Smith, B. (2000). “Traffic flow forecasting using approximate nearest neighbor nonparametric regression.” A research project report for U.S. DOT University transportation center.

Qi, Y. and Smith, B. L. (2004). “Identifying nearest-neighbors in a large-scale incident data archive.” Transportation Research Report, 1879, pp. 89-98.10.3141/1879-11Qi, Y. and Smith, B. L. (2004). “Identifying nearest-neighbors in a large-scale incident data archive.” Transportation Research Report, 1879, pp. 89-98.

Robinson, P. (1983). “Nonparametric estimators for time series.” Journal of Time Series Analysis, Vol. 4, No. 3, pp. 185-207.10.1111/j.1467-9892.1983.tb00368.xRobinson, P. (1983). “Nonparametric estimators for time series.” Journal of Time Series Analysis, Vol. 4, No. 3, pp. 185-207.

Smith, B. L., Williams, B. M. and Oswald, R. K. (2002). “Comparison of parametric and nonparametric models for traffic flow fore-casting.” Transportation Research Part C, Vol. 10, No. 4, pp. 303-321.10.1016/S0968-090X(02)00009-8Smith, B. L., Williams, B. M. and Oswald, R. K. (2002). “Comparison of parametric and nonparametric models for traffic flow fore-casting.” Transportation Research Part C, Vol. 10, No. 4, pp. 303-321.

Stathopoulos and Karlaftis (2003). “A multivariate state-space approach for urban traffic flow modeling and prediction.” Transportation Research Part C, Vol. 11, No. 2, pp. 121-135.10.1016/S0968-090X(03)00004-4Stathopoulos and Karlaftis (2003). “A multivariate state-space approach for urban traffic flow modeling and prediction.” Transportation Research Part C, Vol. 11, No. 2, pp. 121-135.

Vlahogianni, E. I., Karlaftis, M. G. and Golias, J. C. (2005). “Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach.” Transportation Research Part C, Vol. 13, No. 3, pp. 211-234. 10.1016/j.trc.2005.04.007Vlahogianni, E. I., Karlaftis, M. G. and Golias, J. C. (2005). “Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach.” Transportation Research Part C, Vol. 13, No. 3, pp. 211-234.

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, Vol. 43, No. 1, pp. 3-19. 10.1016/j.trc.2014.01.005Vlahogianni, 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, Vol. 43, No. 1, pp. 3-19.

Yoon, B. and Chang, H. (2014). “Potentialities of data-driven non-parametric regression in urban signalized traffic flow forecasting.” Journal of Transportation Engineering, Online.10.1061/(ASCE)TE.1943-5436.0000662Yoon, B. and Chang, H. (2014). “Potentialities of data-driven non-parametric regression in urban signalized traffic flow forecasting.” Journal of Transportation Engineering, Online.