Research And Application Of Double Weighted Grey Model

Scholars have been keen on the study of gray theory, and the improvement of grey prediction model is one of the major hot spots. Most improved mainly in four aspects: the original data model, accumulative generation, background value generation, selection of the initial conditions. Deep background of weighted value of PGM(1.1) model and weighted initial conditions FGM(1.1) model based on the analysis of the study, combined with the background value generation and initial conditions at the same time to improve.Set up double weighted grey prediction at DGM(1.1) model, this model is a unilateral improved model of background value generation, the initial conditions of a summary,covers the background value improvement and initial condition to improve all the content,is a kind of weighted model of upgrade. Test the accuracy of the new model, discussed its application scope. Through examples verify the accuracy is not lower than the first two models, the new model can take the place of the first two, is worth popularization and application.