Improved GM (1, 1) model for sea level change prediction

In the past study of conventional GM (1,1) model for sea level change predictions, as the grey model is exponential function, the change is often very large, lacking of considering the linear factor in the sea level change, thus the linear trend of sea level change should be reasonably reflected. In this paper, an improvement methods, which is adding the linear part to the exponential form expression of GM (1, 1) model to get a grey linear model, is attempted for improving GM (1, 1) model. The data used is the global mean sea level time series data generated by tidal file and provided by Permanent Service for Mean Sea Level. The result shows that the improved model results accuracy is higher than the conventional GM (1, 1) model, the improved model overcomes the disadvantages of conventional GM(1,1) model can not reflect the linear rule of sea level change, and also it makes up for the simple linear model can´t reflect nonlinear trend of sea level change.