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Research on Fault Prediction of Modern Aviation Electronic Equipment Based on Improved Grey Model

DOI: 10.4236/jsea.2013.63B001    2,928 Downloads   4,163 Views   Citations

ABSTRACT

The basic principle and method of Grey Model prediction are presented. In view of the defects of general GM(1,1) model, an improved method is proposed. That is using the particle swarm optimization algorithm to obtain the best forecast dimension and using metabolism to make the model parameters adaptively change. Finally, the improved Grey Model is used to predict the fault of high voltage power supply circuit of a certain type of modern air-borne radar. The results which are computed and simulated by Matlab software show that the forecast precision of improved Grey Model is higher than that of original Grey Model.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

J. Zhou, Q. Jing, X. Xie and N. Zhou, "Research on Fault Prediction of Modern Aviation Electronic Equipment Based on Improved Grey Model," Journal of Software Engineering and Applications, Vol. 6 No. 3B, 2013, pp. 1-3. doi: 10.4236/jsea.2013.63B001.

References

[1] Jianxin Zhang, Lang Wu. An Improved Method for Image Edge Detection Based on GM(1,1) Model [C]. 2009 International Conference on Artificial Intelligence and Computational Intelligence, 2009: 133-136.
[2] Sifeng Liu, Yaoguo Dang, Zhigeng Fang. Grey System Theory and Application, Beijing: Science Press[M], 2010 (in Chinese).
[3] Ziyin Gu. The Application on Population Prediction Based on Metabolism GM(1,1) Model, Statistics and Consultation, vol.4, pp.30-31, 2009. (in Chinese)
[4] A. Banks, J. Vincent, and C. Anyakoha, “A Review of Particle Swarm Optimization. Part I: Background and Development,” Natural Computing, vol.6, no.4, pp.467-484, 2007.
[5] A. Banks, J. Vincent, and C. Anyakoha, “Review of Particle Swarm Optimization. Part II: Hybridization, Combinatorial, Multicriteria and Constrained Optimization, and Indicative Applications,” Natural Computing, vol. 7, no. 1, pp. 109-124, 2008.
[6] Deng Julong, Elements of Grey System Tbeory, Wuhan:Hua zhong University of Science&Technology Press, 2002.(in Chinese)

  
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