Neural Network for Estimating the Main Parameters in Flight Vehicle Preliminary Design

With neural network technology developed rapidly in recent years,three parameter estimating networks for total mass,lift coefficient and drag coefficient are respectively structured successfully that play an important role in flight vehicle preliminary design.The result shows that trained parameter estimating networks can give more accurate value than usual approximating functions.And,according to the characteristics of the data involved here,a modification has been made for promoting the accuracy of MBP algorithm.The simulating result proved that the modified MBP algorithm can work more effectively.This method can be used in other product's preliminary design of machinery,aeronautics and astronautics.