Prediction of irrigation water use using parallel gray neural network

The paper put forward a forecast method named parallel gray neural network (PGNN), which was combined with neural network and the gray forecast method. The PGNN was adopted to forecast irrigation water use and the forecast method availability degree was used as the optimization index to calculate the weighted coefficient of the combination model. The results showed that the average error of PGNN was 2.67% and it was obviously lower than that of unitary gray and neural network forecast method. PGNN can be applied to forecast middle-long term irrigation water use.