DocumentCode :
2745587
Title :
Data-Fusion Forecast Model of Missile Failure Time Based on Artificial Neural Network
Author :
Wang, Liang ; Lv, Weimin ; Jiang, Shiwei
Author_Institution :
Dept. of Airborne Vehicle Eng., Naval Aeronaut. Eng. Inst., Yantai, China
Volume :
2
fYear :
2010
fDate :
5-6 June 2010
Firstpage :
24
Lastpage :
27
Abstract :
Aiming at forecasting failure time of the missile more accurately, saving the manpower, money and material resources, a data-fusion forecast model based on artificial neural network was put forward. First, several single forecasting methods including grey model, time series model and so on were used. Then, all of the single forecast results were fused by artificial neural network. The model was calculated by using Matlab and the final result was get. Experimental results showed that the model achieved better forecast results compared with other forecast models.
Keywords :
grey systems; military computing; missiles; neural nets; sensor fusion; time series; Matlab; artificial neural network; data-fusion forecast model; grey model; missile failure time forecasting; time series model; Artificial neural networks; Computer networks; Failure analysis; Industrial engineering; Mathematical model; Missiles; Predictive models; Regression analysis; Smoothing methods; Vehicles; artificial neural network; data-fusion forecast model; failure time; missile;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Control and Industrial Engineering (CCIE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-4026-9
Type :
conf
DOI :
10.1109/CCIE.2010.124
Filename :
5491973
Link To Document :
بازگشت