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Grain Yield Prediction for Irrigation District Based on Least Squares Support Vector Machine

ZAI Song-mei et al(Farmland Irrigation Research Institute,CAAS,Xinxiang,Henan 453003)  
Commonly used grain yield forecasting models were briefly reviewed,and a yield prediction model of irrigation district was established based on least squares support vector machines.The grain yield in irrigation district was analog calculated.And the test samples were used to compare with gray prediction,and neural network model.The maximum predicted error of least squares SVM was 7.12%,with an average error of 4.81%.The results showed that least squares support vector machine model has high prediction accuracy and strong generalization ability.So it could be used as a new method for irrigation district yield prediction.
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