Prediction of Near-surface Moisture Based on GNN in Heilongjiang Province
Qiumeng Yang · DOAJ (DOAJ: Directory of Open Access Journals) · 2013
According to BP neural network for prediction of soil moisture in the presence of larger space existing in the local extremum,BP neural network was optimized by using GA algorithm.In accordance with the crop root growth and distribution of water situation,the different growth period of soybean,5 strata depths,genetic neural network models were built for prediction of soil moisture.They were applied in Heilongjiang Province reclamation area farm red star soybean field.The results showed that the prediction model of soybean sowing in early 2009 and the whole growth period soil volumetric water content prediction of the mean absolute error was 1.83%,better indicating soybean field soil moisture in specific cases.GA-BP forecast method provided reliable scientific basis for soybean water-saving irrigation and management,and could be used to provide reference of cold soybean or other crops field soil moisture forecast.