Predict China's Per Capita Gdp Based On Ending-Point Optimized Discrete Grey (1,1) Model

In this paper, in view of the disadvantages of traditional discrete GM (1, 1) model, we propose the ending-point optimized discrete grey (1, 1) model (EODGM(1,1)) to improve prediction accuracy and give the concrete calculation formula. The novel model assumes that the sequence start iteration from the optimized ending point. We can get optimum initial iteration point by using optimization algorithm proposed in this paper. Because the ending point stands for the latest information, so the EODGM(1,1) is accord with the new information priority principle. We use the data of China's per capita gross domestic product (GDP) from 2001 to 2009 as an example, and the results show that the simulation accuracy of the EODGM(1,1) is superior to the traditional discrete GM (1,1) and ending-point fixed discrete grey model (EDEGM(1,1)). Furthermore, the one step prediction accuracy and two step prediction accuracy has more obvious advantages. The results show that this novel model is effective and applicable.