Degradation modeling and classification of mixed populations using segmental continuous hidden Markov models
暂无分享,去创建一个
[1] Maxim Finkelstein,et al. Shocks as Burn-In in Heterogeneous Populations , 2012 .
[2] Ren-Hua Wang,et al. Integrating Articulatory Features Into HMM-Based Parametric Speech Synthesis , 2009, IEEE Transactions on Audio, Speech, and Language Processing.
[3] Frédéric Kratz,et al. Methods to choose the best Hidden Markov Model topology for improving maintenance policy , 2012 .
[4] David He,et al. A segmental hidden semi-Markov model (HSMM)-based diagnostics and prognostics framework and methodology , 2007 .
[5] Xiang Li,et al. A Physically Segmented Hidden Markov Model Approach for Continuous Tool Condition Monitoring: Diagnostics and Prognostics , 2012, IEEE Transactions on Industrial Informatics.
[6] Min Xie,et al. Classifying Weak, and Strong Components Using ROC Analysis With Application to Burn-In , 2007, IEEE Transactions on Reliability.
[7] Rajendra Prasad,et al. Comparison of support vector machine, artificial neural network, and spectral angle mapper algorithms for crop classification using LISS IV data , 2015 .
[8] Heiga Zen,et al. Robust Speaker-Adaptive HMM-Based Text-to-Speech Synthesis , 2009, IEEE Transactions on Audio, Speech, and Language Processing.
[9] Michael E. Cholette,et al. Degradation modeling and monitoring of machines using operation-specific hidden Markov models , 2014 .
[10] Jianying Hu,et al. HMM Based On-Line Handwriting Recognition , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[11] Hong-Fwu Yu. Optimal classification of highly-reliable products whose degradation paths satisfy Wiener processes [1] , 2003 .
[12] Chun Su,et al. A Novel Multi-hidden Semi-Markov Model for Degradation State Identification and Remaining Useful Life Estimation , 2013, Qual. Reliab. Eng. Int..
[13] Ji Hwan Cha,et al. Optimal burn-in procedure for mixed populations based on the device degradation process history , 2016, Eur. J. Oper. Res..
[14] George C. Runger,et al. Process Monitoring Using Hidden Markov Models , 2014, Qual. Reliab. Eng. Int..
[15] António Simões,et al. The State of the Art of Hidden Markov Models for Predictive Maintenance of Diesel Engines , 2017, Qual. Reliab. Eng. Int..
[16] H. Kaebernick,et al. Remaining life estimation of used components in consumer products: Life cycle data analysis by Weibull and artificial neural networks , 2007 .
[17] Frédéric Kratz,et al. Failure Event Prediction Using Hidden Markov Model Approaches , 2015, IEEE Transactions on Reliability.
[18] B. Yum,et al. Optimal design of step-stress accelerated degradation tests based on the Wiener degradation process , 2016 .
[19] B. Yum,et al. Optimal design of accelerated degradation tests based on Wiener process models , 2011 .
[20] Tangbin Xia,et al. Optimal multi-level classification and preventive maintenance policy for highly reliable products , 2017, Int. J. Prod. Res..