A probabilistic multi-model Bayesian network for fatigue damage prognosis

[1]  M. Hurn,et al.  Improving the acceptance rate of reversible jump MCMC proposals , 2004 .

[2]  P. C. Paris,et al.  A Critical Analysis of Crack Propagation Laws , 1963 .

[3]  Jaap Schijve,et al.  Fatigue of Structures and Materials in the 20th Century and the State of the Art. , 2003 .

[4]  C. Robert,et al.  Bayesian inference in hidden Markov models through the reversible jump Markov chain Monte Carlo method , 2000 .

[5]  R. Trotta Applications of Bayesian model selection to cosmological parameters , 2005, astro-ph/0504022.

[6]  L. Tierney,et al.  Accurate Approximations for Posterior Moments and Marginal Densities , 1986 .

[7]  Gudfinnur Sigurdsson,et al.  Probabilistic Inspection Planning of the Åsgard A FPSO Hull Structure With Respect to Fatigue , 2000 .

[8]  Sankaran Mahadevan,et al.  Model uncertainty and Bayesian updating in reliability-based inspection , 2000 .

[9]  Ali Fatemi,et al.  Cumulative fatigue damage and life prediction theories: a survey of the state of the art for homogeneous materials , 1998 .

[10]  Michael I. Miller,et al.  REPRESENTATIONS OF KNOWLEDGE IN COMPLEX SYSTEMS , 1994 .

[11]  Rolf Weil,et al.  Low cycle fatigue of thin copper foils , 1996 .

[12]  Andrew D. Dimarogonas,et al.  Vibration of cracked structures: A state of the art review , 1996 .

[13]  P. Goel,et al.  The Statistical Nature of Fatigue Crack Propagation , 1979 .

[14]  P. Green Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .

[15]  John S. J. Hsu Generalized Laplacian approximations in Bayesian inference , 1995 .

[16]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[17]  Karl-Heinz Schwalbe,et al.  Comparison of several fatigue crack propagation laws with experimental results , 1974 .

[18]  B. Carlin,et al.  Bayesian Model Choice Via Markov Chain Monte Carlo Methods , 1995 .

[19]  J. Berger,et al.  The Intrinsic Bayes Factor for Model Selection and Prediction , 1996 .

[20]  Weicheng Cui,et al.  A state-of-the-art review on fatigue life prediction methods for metal structures , 2002 .

[21]  Xuefei Guan,et al.  Probabilistic fatigue damage prognosis using maximum entropy approach , 2012, J. Intell. Manuf..

[22]  G. Roberts,et al.  Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions , 2003 .

[23]  P. Green,et al.  On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion) , 1997 .

[24]  Bradley P. Carlin,et al.  Markov Chain Monte Carlo Methods for Computing Bayes Factors , 2001 .

[25]  Wasserman,et al.  Bayesian Model Selection and Model Averaging. , 2000, Journal of mathematical psychology.

[26]  J. Newman A crack-closure model for predicting fatigue crack growth under aircraft spectrum loading , 1981 .

[27]  Radford M. Neal Annealed importance sampling , 1998, Stat. Comput..

[28]  Robert E. Kass,et al.  Importance sampling: a review , 2010 .

[29]  O. Cappé,et al.  Reversible jump, birth‐and‐death and more general continuous time Markov chain Monte Carlo samplers , 2003 .

[30]  H. Jeffreys,et al.  Theory of probability , 1896 .