Residual life prediction based on dynamic weighted Markov model and particle filtering
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[1] James Kuria Kimotho,et al. Machinery Prognostic Method Based on Multi-Class Support Vector Machines and Hybrid Differential Evolution – Particle Swarm Optimization , 2013 .
[2] Ying Peng,et al. A novel method for online health prognosis of equipment based on hidden semi-Markov model using sequential Monte Carlo methods , 2012 .
[3] Robert Kohn,et al. Auxiliary particle ltering within adaptive Metropolis-Hastings sampling , 2010, 1006.1914.
[4] Jun Wu,et al. Failure time prediction for mechanical device based on the degradation sequence , 2015, J. Intell. Manuf..
[5] Zhengjia He,et al. Remaining life prognostics of rolling bearing based on relative features and multivariable support vector machine , 2013 .
[6] Xing Wang,et al. A dynamic multi-scale Markov model based methodology for remaining life prediction , 2011 .
[7] Rong Li,et al. Residual-life distributions from component degradation signals: A Bayesian approach , 2005 .
[8] Noureddine Zerhouni,et al. CNC machine tool's wear diagnostic and prognostic by using dynamic Bayesian networks , 2012 .
[9] Iqbal Gondal,et al. Multi-step support vector regression and optimally parameterized wavelet packet transform for machine residual life prediction , 2013 .
[10] Dustin G. Mixon,et al. On a Markov‐modulated shock and wear process , 2009 .
[11] Kwok L. Tsui,et al. A naive Bayes model for robust remaining useful life prediction of lithium-ion battery , 2014 .
[12] Ping Yi Chao,et al. An improved neural network model for the prediction of cutting tool life , 1997, J. Intell. Manuf..
[13] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .
[14] Steven M. Cox,et al. Stochastic models for degradation-based reliability , 2005 .
[15] Sami Ekici,et al. Support vector machines models for surface roughness prediction in CNC turning of AISI 304 austenitic stainless steel , 2012, J. Intell. Manuf..
[16] Marcos Eduardo Orchard,et al. A Particle Filtering-based Framework for On-line Fault Diagnosis and Failure Prognosis , 2007 .
[17] Chaochao Chen,et al. Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach , 2012 .
[18] Enrico Zio,et al. Ensemble neural network-based particle filtering for prognostics , 2013 .
[19] Zhigang Tian,et al. An artificial neural network method for remaining useful life prediction of equipment subject to condition monitoring , 2012, J. Intell. Manuf..