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Exponential smoothing is one of the most commonly used prediction methods. When the data has obvious periodicity and seasonality, Holt–Winters usually has a good prediction performance. However, the predicted results often do not meet our expectations when the trend of the original data is not clear. To further reduce the randomness of time series, a new method combining grey generating operator with the traditional Holt–Winters is proposed. The accumulated sequence by grey generating operator can have obvious variation law. Three practical examples were selected to evaluate the forecasting performance of this proposed method. The results indicate that the proposed model can substantially have the better forecasting capability than traditional Holt–Winters method.

Holt–Winters model with grey generating operator and its application