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Proceedings Paper

Avionics equipment failure prediction based on genetic programming and grey model
Author(s): Xiujian Deng; Qiang Luo; Yiyang Zhao; Qi Feng
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Paper 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.

Paper Details

Date Published: 23 January 2017
PDF: 7 pages
Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103220C (23 January 2017); doi: 10.1117/12.2265227
Show Author Affiliations
Xiujian Deng, Science and Technology on Avionics Integration Lab. (China)
Qiang Luo, Northwestern Polytechnic Univ. (China)
Yiyang Zhao, Northwestern Polytechnic Univ. (China)
Qi Feng, Northwestern Polytechnic Univ. (China)

Published in SPIE Proceedings Vol. 10322:
Seventh International Conference on Electronics and Information Engineering
Xiyuan Chen, Editor(s)

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