径向基函数具有良好的逼近任意非线性函数和表达系统内在的难以解析的规律性的能力,并且具有极快的学习收敛速度。基于径向基函数网络的在预测非线性数据上的优点,我们可以将其用于汽车销量的预测。 Radial basis functions have a good ability to approximate any nonlinear function and express the inherent inability to interpret the regularity of the system, and have an extremely fast learning convergence rate. Based on the advantages of radial basis function networks in predicting non-linear data, we can use it for the prediction of car sales.