Forecasting foreign tourist arrivals in India using a single time series approach based on rough set theory
by Kriti Kumari; Haresh Kumar Sharma; Shalini Chandra; Samarjit Kar
International Journal of Computing Science and Mathematics (IJCSM), Vol. 16, No. 4, 2022

Abstract: In this study, a hybrid approach based on single forecasts and rough set theory (RST) is proposed for forecasting foreign tourist arrivals (FTAs) to India. In the formulation of the proposed hybrid method, the FTAs time series data is first forecasted using four time series models: Naive I, Naive II, Grey, and vector error correction (VEC) models. Then the RST is applied to generate an appropriate weight coefficient and the single forecasting results are combined via the weight coefficient. The study also compares the forecasting results of the hybrid method with single forecasts and other combination methods such as the simple average (SA) and the inverse of the mean absolute percentage error (IMAPE). Empirical results show that the proposed hybrid approach performs better than the other single forecasting models.

Online publication date: Wed, 01-Feb-2023

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