Affiliations: [a] Department of Mathematics, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, India | [b] Department of Mathematics, LMNO, Universite de caen-Normandie, Caen, France
Correspondence:
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Corresponding author: Khadar Babu, Department of Mathematics, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India. E-mail: [email protected].
Abstract: When trend and seasonality are detected, the Holt-Winters multiplicative approach is one of the most commonly used methods for forecasting time series data. Choosing the proper initial values for level, trend, and seasonality plays a vital role in this method. In this paper, a new and efficient procedure to choose the initial values for the Holt-Winters multiplicative method is developed. A total of 12 types of agricultural satellite backscatter values are used for analysis, estimated, and compared with the existing Hansun and Holt-Winters methods and the proposed initial setting method with the best smoothing constants. According to the analysis of the mean absolute percentage error, symmetric mean absolute percentage error, Theil-U statistics, and root mean squared error, the proposed approaches outperformed the existing methods in this experiment.
Keywords: Weighted moving average, time series forecasting, initial conditions, hansun method, Holt-Winters method
