DocumentCode
507961
Title
Forecast Model of Vehicle Effectiveness Based on Factors Analysis and RBF Neural Networks
Author
Li, Guoqiang ; Ren, Shuangying
Author_Institution
Dept. of Technol. Support Eng., Acad. of Armored Force Eng., Beijing, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
Effectiveness forecast of especial vehicle is important in vehicle development and compare research. This paper establishes forecast model of vehicle effectiveness by factors analysis with interpretability, and RBF (radial basis function) neural networks with short training time and precise function. Secondly, the result of forecasted and original is contrasted together, then the quality and creditability of forecast model can be verified.
Keywords
radial basis function networks; traffic engineering computing; vehicles; RBF neural networks; factors analysis; radial basis function neural networks; vehicle effectiveness forecast model; Automotive engineering; Demand forecasting; Neural networks; Paper technology; Predictive models; Radial basis function networks; Regression analysis; Technology forecasting; Time series analysis; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5364243
Filename
5364243
Link To Document