RBF神经网络在可溶性糖含量预测中的应用

Application of RBF Neural Network for Predicting Soluble Sugar Content

在小麦(Triticum aestivum L.)幼苗生长过程中,将RBF神经网络应用到可溶性糖含量的预测和数据变化的分析中,试验数据经过RBF神经网络的训练和仿真后得到,网络输出结果的误差小,网络输出矢量与目标矢量相关性好。说明可以将RBF神经网络作为农作物幼苗生长中预测数据变化的有效方法。

RBF neural network was applied for prediction of soluble sugar content and analysis of data change during the growth of seedling.After the data been trained and simulated by neural network,the error of network output was little while the correlation of output vector and target vector was good,indicating that RBF neural network could be an effective method for forecasting data change in seeding growth of crops.