Grey - neural network combination forecast model of the world food consumption

This paper puts forward a world food consumption forecast method, which is based on grey - neural network combination forecast model. Firstly, we make predictions according to the original data by using GM(1,1) and BP neural network respectively. Then we introduce proper weights and establish the grey - neural network combination forecast model. Finally, we get the results. Example proves that the method can raise forecast accuracy effectively and is a very effective and much more accurate grain consumption forecast model.