Abstract: In this paper, a modified grey wave forecasting model with generalized contour lines is proposed to forecast time series which is increasing (or decreasing) and fluctuating with time. The modified model identifies the slope of contour lines through a linear regression model with time trend and estimates the regression model with ordinary least square method. And then a set of parallel lines between the minimum and maximum values of original data series are chosen as the generalized contour lines. In the last step, GM(1,1) models are established based on the elements in generalized contour time sequences. In the empirical analysis, the proposed model is used to forecast Chinese airline passenger volume, which fluctuates with increasing trend and crude oil price, which fluctuates with decreasing trend in the past several months. The result indicates that grey wave forecasting model with generalized contour lines can improve the accuracy of grey wave forecasting model with horizontal contour lines. Also it is useful to forecast the development of emerging things, since it just uses relatively few sample data.

Key words: grey wave forecasting, generalized contour lines, airline passenger volume, crude oil price