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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.

has been cited by the following article:

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

  AUTHORS: Junjie Zhou, Qigen Jing, Xinhua Xie, Naidong Zhou

  KEYWORDS: Grey Model; Fault Prediction; Modern Aviation Electronic Equipment

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.6 No.3B, April 10, 2013

  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.