Ensemble of Data-Driven Prognostic Algorithms with Weight Optimization and K-Fold Cross Validation
暂无分享,去创建一个
[1] J.W. Hines,et al. Prognostic algorithm categorization with PHM Challenge application , 2008, 2008 International Conference on Prognostics and Health Management.
[2] Krishna R. Pattipati,et al. Model-Based Prognostic Techniques Applied to a Suspension System , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[3] L. Cooper,et al. When Networks Disagree: Ensemble Methods for Hybrid Neural Networks , 1992 .
[4] Jing Pan,et al. Prognostic Degradation Models for Computing and Updating Residual Life Distributions in a Time-Varying Environment , 2008, IEEE Transactions on Reliability.
[5] Geir Evensen,et al. The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .
[6] Rommert Dekker,et al. Applications of maintenance optimization models : a review and analysis , 1996 .
[7] George Eastman House,et al. Sparse Bayesian Learning and the Relevance Vector Machine , 2001 .
[8] Masoud Rais-Rohani,et al. Ensemble of Metamodels with Optimized Weight Factors , 2008 .
[9] T. Leibfried,et al. Online monitors keep transformers in service , 1998 .
[10] J. A. García-Souto,et al. Measurements of mechanical vibrations at magnetic cores of power transformers with fiber-optic interferometric intrinsic sensor , 2000, IEEE Journal of Selected Topics in Quantum Electronics.
[11] Matthew J. Watson,et al. ELECTROCHEMICAL CELL DIAGNOSTICS USING ONLINE IMPEDANCE MEASUREMENT, STATE ESTIMATION AND DATA FUSION TECHNIQUES , 2001 .
[12] R. Haftka,et al. Ensemble of surrogates , 2007 .
[13] Daisuke Kihara,et al. EMD: an ensemble algorithm for discovering regulatory motifs in DNA sequences , 2006, BMC Bioinformatics.
[14] Bhaskar Saha,et al. Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework , 2009, IEEE Transactions on Instrumentation and Measurement.
[15] Jianbo Yu,et al. A similarity-based prognostics approach for Remaining Useful Life estimation of engineered systems , 2008, 2008 International Conference on Prognostics and Health Management.
[16] Kai Goebel,et al. Fusing Competing Prediction Algorithms for Prognostics (Preprint) , 2006 .
[17] S. Rahman,et al. Decomposition methods for structural reliability analysis , 2005 .
[18] Lubica Benusková,et al. Organization of the state space of a simple recurrent network before and after training on recursive linguistic structures , 2007, Neural Networks.
[19] F.O. Heimes,et al. Recurrent neural networks for remaining useful life estimation , 2008, 2008 International Conference on Prognostics and Health Management.
[20] Enrico Zio,et al. A data-driven fuzzy approach for predicting the remaining useful life in dynamic failure scenarios of a nuclear system , 2010, Reliab. Eng. Syst. Saf..
[21] Abhinav Saxena,et al. Damage propagation modeling for aircraft engine run-to-failure simulation , 2008, 2008 International Conference on Prognostics and Health Management.
[22] VectorRegressionAlex J. Smola. A Tutorial on Support Vector Regression Produced as Part of the Esprit Working Group in Neural and Computational Learning Ii, Neurocolt2 27150 , 1998 .
[23] Mark Schwabacher,et al. A Survey of Data -Driven Prognostics , 2005 .
[24] K. Goebel,et al. Fusing competing prediction algorithms for prognostics , 2006, 2006 IEEE Aerospace Conference.
[25] Alaa Elwany,et al. Residual Life Predictions in the Absence of Prior Degradation Knowledge , 2009, IEEE Transactions on Reliability.
[26] Wei Wang,et al. Construct support vector machine ensemble to detect traffic incident , 2009, Expert Syst. Appl..
[27] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[28] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.