Abstract: Because of the complex series of phase and physical change,as well as large amounts of data in hot rolling of steel strip production process,the basic method of data mining can be used to model,extract rules and achieve the performance prediction and function evaluation of hot rolling strip production.The article uses radial basis function (RBF) neural network to model,and implement the performance prediction of hot rolling strip production.The RBF neural network is better than the traditional BP neural network when considering approximation capabilities,learning rate and so on.This paper shows the superiority of RBF neural network according to the network structures of RBF and BP.

Key words: hot rolling steel, radial basis function neural network, BP neural network