The difficulty of the prediction
of military aircraft purchase price lies in the small sample data, and the sample
data have the complicated non-linear characteristics. By analyzing the influence
of parameters of aircraft purchase price, SVR is proposed to predict the aircraft
purchasing price model, and uses the model to predict the aircraft purchase price.
The calculation results show that the prediction of the purchase price to establish
military aircraft model has higher prediction accuracy.
Cite this paper
Tong, J. , Du, J. , Chen, P. , Yuan, J. and Huan, Z. (2015) The Price Forecasting of Military Aircraft Based on SVR. Journal of Computer and Communications
, 234-237. doi: 10.4236/jcc.2015.35030
 Vapnik, V N. (1999) An Overview of Statistical Learning Theory. IEEE Trans. on Neural Network, 10, 988-999.
 Schlkopf, B., et al. (2000) New Support Vector Algorithms. Neural Computation, 12, 1207-1245.
 Chen, Q., Wu, M.C., Xue, Y.J., Yang, J.F. and Liu, G.Y. (2009) Carbon Flux Based on Support Vector Regression Prediction. Computer Engineering and Applications, 45, 235-238. (In Chinese)
 Li, D.Q. (2009) Application of Support Vector Machine Regression Method in Prediction of Ship’s Price Index. Ship & Ocean Engineering, 2, 104-106. (In Chinese)
 Lian, C.B., Zhao, Y.J., Li, H.L., Qu, F., Cai, F.L. and Zhang, J.T. (2008) Based on Support Vector Machine Regression Prediction of Coalbed Gas Content. J. Xi’an University of Science and Technology, 28, 707-710. (In Chinese)
 Li, R. and Li, G.M. (2008) Predict the Output of Photovoltaic Power Generation Based on Support Vector Machine Regression. China Electric Power, 41, 74-78. (In Chinese)