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Precipitation prediction is the core of a regional drought prediction. Due to the great randomness and uncertainty in the precipitation process, this study combined the grey model and BP artificial neural network. The residual errors of precipitation were modified by the BP artificial neural network after the precipitation were modeled and predicted by the grey model, then the grey-BP neural network combination model was established for predicting the precipitation in the studied area. The results showed that the prediction accuracy of the combination model was the highest by integrating the advantages of the grey model and BP artificial neural network. The prediction error of the combination model was much lower than the grey model’s and only slightly lower than the BP neural network model’s.

The Application of Gray Model and BP Artificial Neural Network in Predicting Drought in the Liaoning Province