Journal
INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS
Volume 16, Issue 4, Pages 340-354Publisher
INDERSCIENCE ENTERPRISES LTD
DOI: 10.1504/IJCSM.2022.128652
Keywords
hybrid approach; time series forecasting; tourist arrivals; single forecasts; rough set; seasonality; multivariate models; weight coefficient
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In this study, a hybrid approach based on single forecasts and rough set theory is proposed to forecast foreign tourist arrivals to India. The results show that the proposed hybrid method performs better than other single forecasting models.
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.
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