Prediction of military UAV development cost based on partial least-square regression method

The basic model was formulated based on the partial least-squares regression method, which has some prominent advantages in dealing with small sample and variables with multiple correlations, and the arithmetic steps of the development cost prediction of the military unmanned air vehicle were given, for there are some complex factors such as maximum take-off mass, cruise velocity,  flight altitude and so on affecting the development cost of the military unmanned air vehicle and few sample data of the military unmanned air vehicle. The data in reference [2] was tested and compared with step multivariate regression, back propagation and radial basis function neural network method. The results show that the partial leastsquares regression model is practical and efficient.