Huang CY, Lu CY and Chen CI
The Grey model is characterized by basic mathematics and a need for few raw data, but it also lacks the flexibility to adjust the model to increase the precision for the forecasting model. This article shows two types of grey forecasting models, GM(1,1) and NGBM. The GM(1,1) shows its fitting ability to the linear raw data and NGBM is superior in fitting nonlinear raw data. In this article, two practical cases are shown to demonstrate the calculation procedures of both models. The results show they are feasible in forecasting.
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