The Influence of Parameters on Prediction Accuracy of ANN Model for Winter Wheat Scab

By dint of optimum correlation method the predictors,which are good indicators of winter wheat scab occurrence in Taihu area in Jiangsu province,were input into the feed forward multi-layer artificial neural network(ANN) based on back-propagation study.ANN prediction model for occurrence of winter wheat scab was developed.The influence of model parameters on the fitting and prediction accuracy of model was studied.It can be concluded that total error square sum(E) has the most outstanding impact on model function than other parameters.The smaller is the value of E,the higher is fitting accuracy for historical samples.Extreme small E will result in lower prediction accuracy for independent samples.The action of number of neurons in the hidden layer (N_h),study factor( α) and momentum factor (β) may be ignored when suitable E was given to make model stable.

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