Electronics Optics & Control, Volume. 25, Issue 12, 102(2018)
Application of Blind Number and GM(1,1) Model in the Reliability Analysis of Performance Degradation Product
[1] [1] ZIO E.Reliability engineering: old problems and new challenges[J].Reliability Engineering and System Safety, 2009, 94: 125-141.
[2] [2] WU L F, LIU S F, YAO L G, et al.The effect of sample size on the grey system model[J].Applied Mathematical Modelling, 2013, 37(1): 6577-6583.
[6] [6] MARKOVIC D, JUKIC D, BENSIC M.Nonlinear weighted least squares estimation of a three-parameter Weibull density with a nonparametric start[J].Journal of Computational and Applied Mathematics, 2009, 228(1): 304-312.
[7] [7] YANG F, YUE Z F.Kernel density estimation of three-parameter Weibull distribution with neural network and genetic algorithm[J].Applied Mathematics and Computation, 2014, 247(1): 803-814.
[8] [8] DENG J L.Proving GM(1,1) modeling via four data(at least)[J].Journal of Grey System, 2004, 16(1): 1-4.
[10] [10] XIE N M,LIU S F.Novel methods on comparing grey numbers[J].Applied Mathematical Modelling, 2010, 34(2): 415-423.
[11] [11] HSU L C, WANG C H.Forecasting the output of integrated circuit industry using a grey model improved by the Bayesian analysis[J].Technological Forecasting and Social Change, 2007, 74(6): 843-853.
Get Citation
Copy Citation Text
GAI Binliang, TENG Kenan, WANG Haowei, CHEN Yu, SUN Yuan. Application of Blind Number and GM(1,1) Model in the Reliability Analysis of Performance Degradation Product[J]. Electronics Optics & Control, 2018, 25(12): 102
Category:
Received: Nov. 7, 2017
Accepted: --
Published Online: Jan. 13, 2021
The Author Email: