The Optimization of Background Value in Non-Equidistant GM(1,1) Model

As the background value is an important factor affecting the precision of grey system model,this paper makes a research on the background value in non-equidistant GM(1,1) model.Based on index characteristic of grey model and the definition of integral,we use the discrete function with non-homogeneous exponential law to fit the accumulated sequence to propose a new method to optimize the background value in non-equidistant GM(1,1) model.The example indicates the precision of simulation and forecast by this optimized background value is obviously higher.This new formula of background value is mot only suitable in non-equidistant GM(1,1) model,but also in equidistant GM(1,1) model,and has high precision and wide applicability.