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 （LS-SVM）. The grain yield in irr...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 （LS-SVM）. 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 LS-SVM model has high prediction accuracy and strong generalization ability. So it could be used as a new method for irrigation district yield prediction展开更多
基金Supported by 863 Plan Project of China(2006AA100213)And theSupport Plan Project of National Science and Technology(2007BAD38B04)~~
文摘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 （LS-SVM）. 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 LS-SVM model has high prediction accuracy and strong generalization ability. So it could be used as a new method for irrigation district yield prediction
