Selection of grey forecasting models for forecasting the number of inbound tourists to Iran
| Grey forecasting models | The reason for selection the model |
|---|---|
| GM(1,1) | The basic grey model, suitable for monotonic trends |
| RGM(1,1) (Rolling GM(1,1)) | An extension of GM(1,1) that dynamically updates the model as new data becomes available, improving accuracy in nonstationary time series |
| Unbiased GM(1,1) | Another extension of GM(1,1) that incorporates an unbiased mechanism to enhance forecasting performance |
| Modified unbiased GM(1,1) | A refined version of Unbiased GM(1,1) with additional adjustments to further eliminate bias and enhance forecasting precision |
| DGM(1,1) (Discrete Grey Model) | Represents the discrete version of the grey model, employing a first-order finite difference equation with a single variable |
| Grey Verhulst Model | Designed for S-shaped growth patterns, suitable for tourism demand that might exhibit an initial slow growth, followed by rapid expansion, and eventual saturation |
| Grey forecasting models | The reason for selection the model |
|---|---|
| GM(1,1) | The basic grey model, suitable for monotonic trends |
| RGM(1,1) (Rolling GM(1,1)) | An extension of GM(1,1) that dynamically updates the model as new data becomes available, improving accuracy in nonstationary time series |
| Unbiased GM(1,1) | Another extension of GM(1,1) that incorporates an unbiased mechanism to enhance forecasting performance |
| Modified unbiased GM(1,1) | A refined version of Unbiased GM(1,1) with additional adjustments to further eliminate bias and enhance forecasting precision |
| DGM(1,1) (Discrete Grey Model) | Represents the discrete version of the grey model, employing a first-order finite difference equation with a single variable |
| Grey Verhulst Model | Designed for S-shaped growth patterns, suitable for tourism demand that might exhibit an initial slow growth, followed by rapid expansion, and eventual saturation |
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