Farnum .N.R, L. W. S. (1989). Quantitative forecasting methods. In: PWS-Kent Publishing Company.
Huo, Y. (2019). Analysis of intelligent evaluation algorithm based on english diagnostic system. Cluster Computing, 22(6), 13821-13826.
Liu, Y., Li, W., Wang, C., & Zhao, J. (2021). Research on Classroom Evaluation Algorithm Based on CNN Text Preprocessing, Cham.
Mentzer, J. T. (1988). Forecasting with adaptive extended exponential smoothing. Journal of the Academy of Marketing Science, 16(3), 62-70.
Monfared, M. A. S., Ghandali, R., & Esmaeili, M. (2014). A new adaptive exponential smoothing method for non-stationary time series with level shifts. Journal of industrial engineering international, 10(4), 209-216.
Nazim, A., & Afthanorhan, A. (2014). A comparison between single exponential smoothing (SES), double exponential smoothing (DES), holt’s (brown) and adaptive response rate exponential smoothing (ARRES) techniques in forecasting Malaysia population. Global Journal of Mathematical Analysis, 2(4), 276-280.
Serin, F., Alisan, Y., & Kece, A. (2021). Hybrid time series forecasting methods for travel time prediction. Physica A: Statistical Mechanics and its Applications, 126134.
Smith, D. E. (1974). Adaptive response for exponential smoothing: Comparative system analysis. Journal of the Operational Research Society, 25(3), 421-435.
Taylor, J. W. (2004). Smooth transition exponential smoothing. Journal of Forecasting, 23(6), 385-404.
Trigg, D. (1964). Monitoring a forecasting system. OR, 15(3), 271-274.
Trigg, D., & Leach, A. (1967). Exponential smoothing with an adaptive response rate. Journal of the Operational Research Society, 18(1), 53-59.