Application of improved grey GM(1,1) model in tourism revenues prediction

Abstract

The GM(l,l) model is the kernel of grey system which can point at the small sample data and uncertain information to predict, and is applied widely in prediction. However, the general grey model is disturbed by old information, which is inadequate to predict accurately. So it is necessary to replace old information with new information. An improved grey model is proposed in this paper, which can realize by amending exponent of the GM(l,l) model. Finally, the improved model and general method were respectively applied to predict Jingdezhen's tourism revenues from 2003 to 2010. The result shows that the improved model can improve prediction precision and obtain a much better prediction result.

Forecasting key indicators of China's inbound and outbound tourism: optimistic–pessimistic method

“…The method proposed in the current study is simple and can be applied with confidence without much tailoring of the original algorithm of grey models. Further, considering the fact that old information can also increase forecast errors in grey models (Juan, 2011;Liu et al, 2014), a new method to confirm it has been proposed. The proposed technique can be easily integrated into any forecasting technique, and increase or decrease in forecast accuracy resulting from this integration reveals the extent of influence of old information on a forecast.…”