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
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;
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
DOI :
10.1109/CISE.2009.5364243
