期刊文献+

Partial Improvement of Traditional Grey-Markov Model and Its Application on Fault Prediction 被引量:1

Partial Improvement of Traditional Grey-Markov Model and Its Application on Fault Prediction
下载PDF
导出
摘要 Modeling experiences of traditional grey-Markov show that the prediction results are not accurate when analyzed data are rare and fluctuated.So it is necessary to revise or improve the original modeling procedure of the grey-Markov(GM)model.Therefore,a new idea is brought forward that the Markov theory is used twice,where the first time is to extend the original data and the second to calculate and estimate the residual errors.Then by comparing the original data sequence from a fault prediction case with the simulation sequence produced by the use of GM(1,1) and the new GM method,results are conforming to the original data.Finally,an assumption of GM model is put forward as the future work. Modeling experiences of traditional grey-Markov show that the prediction results are not accurate when analyzed data are rare and fluctuated. So it is necessary to revise or improve the original modeling procedure of the grey-Markov (GM) model. Therefore, a new idea is brought forward that the Markov theory is used twice, where the first time is to extend the original data and the second to calculate and estimate the residual errors. Then by comparing the original data sequence from a fault prediction case with the simulation sequence produced by the use of GM(1,1) and the new GM method, results are conforming to the original data. Finally, an assumption of GM model is put forward as the future work.
出处 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2017年第4期449-455,共7页 南京航空航天大学学报(英文版)
基金 supported by the National Natural Science Foundation of China(No.61303098)
关键词 grey-Markov model GM(1 1) residual error grey-Markov model GM(1,1) residual error
  • 引文网络
  • 相关文献

参考文献6

二级参考文献51

  • 1王巍,张桂才,骆玉玲.光纤陀螺误差分析及其抑制措施[J].导弹与航天运载技术,1994(2):29-35. 被引量:4
  • 2Gerritsen,H.,de Vries,H.,and Philippart,M.,1995.The dutch continental shelf model.In:Quantitative Skill Assessment for Coastal Ocean Model,Coastal Estuarine Studies.AGU,Washington,D.C.,47:425-467.
  • 3Lee,T.-L.,2009.Predictions of typhoon storm surge in Taiwan using artificial neural networks.Advances in Engineering Software,40:1200-1206.
  • 4Liu,S.F.,Dang,Y.G.,and Fang,Z.G.,2004.Grey System Theory andIts Applications.Science Press,Beijing,125-162.
  • 5Madsen,H.,and Jakobsen,F.,2004.Cyclone induced storm surge and flood forecasting in the northern Bay of Bengal.Coastal Engineering,51:277-296.
  • 6Papoulis,A.,and Pillai,S.U.,2002.Probability,Random Variables and Stochastic Processes.Mcgraw Hill Higher Education,New York.
  • 7Vested,H.J.,Nielsen,H.R.,Jensen,H.R.,and Kristensen,K.B.,1995.Skill assessment of an operational hydrodynamic forecast system for the North Sea and Danish Belts.Coastal and Estuarine Studies,47:373-396.
  • 8Von Storch,H.,G(6)nnert,G.,and Meine,M.,2008.Storm surges-An option for Hamburg,Germany,to mitigate expected future aggravation of risk.Environmental Science and Policy,11:735-742.
  • 9Woodworth,P.L.,Flather,R.A.,Williams,J.A.,Wakelin,S.L.,and Jevrejeva,S.,2007.The dependence of UK extreme sea levels and storm surges on the North Atlantic Oscillation.Continental Shelf Research,27:935-946.
  • 10Zhu,C.Q.,2001.Grey prediction modeling via grey relational weighting.The Journal of Grey System,13 (3):189-193.

共引文献31

同被引文献1

引证文献1

二级引证文献2

;
使用帮助 返回顶部