基于RBF神经网络的农田土壤含盐量预测

Prediction of Farm Soil Salt Content Based on Radial Basis Function Neural Network

介绍了径向基函数神经网络的原理、训练算法,并建立了基于径向基函数神经网络的农田土壤含盐量预测模型。通过实例验证,该模型具有较强的非线性处理能力和逼近能力,运算速度快,性能稳定,预测精度较高,泛化能力强,可用于生产实践中。

The principle of radial base function neural network and its train algorithm are introduced in this paper.Meanwhile,the model of soil salt content prediction based on radial base function neural network is established.An example is given to prove that the model has stronger nonlinear handling ability and approach ability,rapid operation speed,stable performance,higher forecast precision and strong fan melt ability,and can be applied to practice.