Application of the Artificial Neural Network to Forecast the Moth-eaten Ratio of Leguminivora Glycinivorella Mats
Leguminivora glycinivorella Mats is one of the main pests of heilongjiang soybean, moth - eaten ratio can be as a forecast index. It is influenced by various factors such as wintering base and weather conditions. It is a complex nonlinear non - normal system. According to basic principle of artificial neural network modeling, neural network prediction model based on the data in Shuangcheng city , Heilongjiang province was established. The model prediction and back - test accuracy were both higher. Thus it can be a new prediction method of moth - eaten ratio of Leguminivora glycinivorella Mats.
NETL
NSTL
万方数据
维普
