Abstract: Hydraulic valve system is a complex system with multiple characteristics affected by multiple geometric elements. It will be essentially important to the manufacture process to establish the prediction model of the system characteristics by using the geometric elements and achieve the goal of prediction. On the basis of synthesizing the features of the back propagation (BP) neural network and RBF neural network, a prediction model which is a new hybrid neural network based on the BP neural network and radial basis function (RBF) neural network is presented. And the hybrid neural network is trained by using data measured from actual production. The calculation results show that the hybrid neural network prediction model can improve the prediction accuracy of a single neural network model, and reach an average relative error of 0.046 1. Therefore the proposed hybrid neural network can well satisfy the requirement of predicting the hydraulic valve characteristics.

Key words: Combined prediction model, Hybrid neural network, Hydraulic valve system, Multiple geometric elements