23 January 2017 Avionics equipment failure prediction based on genetic programming and grey model
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Proceedings Volume 10322, Seventh International Conference on Electronics and Information Engineering; 103220C (2017) https://doi.org/10.1117/12.2265227
Event: Seventh International Conference on Electronics and Information Engineering, 2016, Nanjing, China
Abstract
Avionics equipment failure prediction by conventional GM (Grey Model) may yield large forecasting errors. Combining GM (1, 1) model with genetic programming algorithm, a kind of GP-GM (1, 1) forecast model was established to minimize such errors. Forecasting sequence was calculated by means of GM (1, 1) model, then genetic programming algorithm was used to modify them further, and the degradation trend prediction of characteristic parameters of avionics equipment was realized. The validity of GP-GM (1, 1) prediction model was testified by tracking and forecasting the experiment data of avionics equipment in real environment.
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Xiujian Deng, Xiujian Deng, Qiang Luo, Qiang Luo, Yiyang Zhao, Yiyang Zhao, Qi Feng, Qi Feng, } "Avionics equipment failure prediction based on genetic programming and grey model", Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103220C (23 January 2017); doi: 10.1117/12.2265227; https://doi.org/10.1117/12.2265227
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