DocumentCode :
1989667
Title :
Aero-generator trend analysis based on optimized grey prediction model
Author :
Cui, Jianguo ; Zhao, Pengyuan ; Dong, Shiliang ; Liu, Liqiu ; Lv, Rui ; Li, Zhonghai
Author_Institution :
Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China
fYear :
2011
fDate :
16-18 Sept. 2011
Firstpage :
3339
Lastpage :
3342
Abstract :
In order to accurately analyze the trend of health state variation of aero-generator, a grey prediction model based on genetic algorithm is presented in this paper. Then use the original grey model and the optimized grey model respectively to carry out health state trend analysis of the aero-generator. On this basis, the two models were used to study aero-generator health trends, and compared with the prediction result of the BP neural network, and find suitable algorithms for aero-generator health trend analysis and prediction.
Keywords :
avionics; backpropagation; genetic algorithms; grey systems; BP neural network; aero-generator health trend analysis; aero-generator health trends; aero-generator trend analysis; genetic algorithm; health state trend analysis; health state variation; optimized grey model; optimized grey prediction model; Analytical models; Atmospheric modeling; Data models; Genetic algorithms; Mathematical model; Optimization; Predictive models; Aero-generator; Genetic algorithm; Grey model; Health state; Oil-filled pressure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8162-0
Type :
conf
DOI :
10.1109/ICECENG.2011.6057830
Filename :
6057830
Link To Document :
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