A Study on the Forecast Model of Dendrolimus punctatus Occurrence Based on Artificial Neural Network

The principle and methodology of artificial neural network were used to select some meteorological factors closely correlated to the occurrence area, population density and damage rate by the methods of correlation coefficients and step regression. The BP network models of meteorological factors and occurrence area, population density and damage rate of Dendrolimus punctatus were established. The results showed that these BP models established have satisfied fitting and forecast precision. When the amount of implicit layer neuron is 15 and the amount of forecast factor is 8, the mean error of forecast of 2 groups of reserved occurrence zone was 3.15% in two years. When the amount of implicit layer neuron is 8 and the amount of forecast factor is 6,the mean error of forecast of reserved occurrence zone was 5.91%, while when the amount of implicit layer neuron is 4 and the amount of forecast factor is 5, the mean error of forecast of reserved occurrence zone was 10.65%.