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An Ensemble Approach for Model Bias Prediction
Journal Article
2013-01-1387
ISSN: 1946-3979, e-ISSN: 1946-3987
Sector:
Citation:
Xi, Z., Fu, Y., and Yang, R., "An Ensemble Approach for Model Bias Prediction," SAE Int. J. Mater. Manf. 6(3):532-539, 2013, https://doi.org/10.4271/2013-01-1387.
Language:
English
References
- Hill , R.G. and Trucano , T.G. Statistical validation of engineering and scientific models: Background Sandia National Laboratories 1999 SAND99-1256
- Thacker , B.H. , Doebling , S.W. , Hemez , F.M. , Anderson , M.C. , Pepin , J.E. , and Rodriguez , E.A. Concepts of model verification and validation Los Alamos National Lab. Los Alamos 2004 LA-14167
- Babuska , I. and Oden , J.T. Verification and validation in computational engineering and science: basic concepts Comput. Methods Appl. Mech. Engrg. 193 2004 4057 4066
- Xiong , Y. , Chen , W. , Tsui , K.L. , and Apley D.W. A Better Understanding of Model Updating Strategies in Validating Engineering Models Comput. Methods Appl. Mech. Engrg. 198 2009 1327 1337
- Chen , W. , Tsui , K. , and Wang , S. A design-driven validation approach using bayesian prediction models J. Mech. Des. 140 2008 021101
- Li , J. , Mourelatos , Z.P. , Kokkolaras , M. , and Papalambros P.Y. Validating designs through sequential simulation-based optimization ASME 2010 International Design engineering Technical Conferences & Computers and Information in Engineering Conference Aug. 15 18 2010 Montreal, Quebec, Canada
- Kennedy , M.C. , and O'Hagan , A. Bayesian calibration of computer models J. Roy. Statist. Soc , Ser. B 63 2001 425 464
- Xi , Z. , Fu , Y. , and Yang , R.J. Validation of computational models in the design space under uncertainty International Journal of Performability Engineering 2012
- Sklar A. Fonctions de répartition à n dimensions et leurs marges Publications de I'Institut de Statistique de l'Université de Paris 8 1959 229 231
- Huard D. , Evin G. , and Favre , A. C. Bayesian Copula Selection Computational Statistics & Data Analysis 51 2 2006 809 822
- Roser B. N. An Introduction to Copulas Springer 1999 New York
- Fermanian J. D. Goodness-of-Fit Tests for Copulas J. Multivariate Anal. 95 2005 119 152
- Chen X. , and Fan Y. Pseudo-likelihood Ratio Tests for Semiparametric Multivariate Copula Model Selection La Revue Canadienne de Statistique 33 3 2005 389 414
- Panchenko V. Goodness-of-Fit Test for Copulas Physica A: Statistical Mechanics and its Applications 355 1 2005 176 182
- Jaynes E. T. , and Bretthorst G. L. Probability Theory: The Logic of Science Cambridge University Press Cambridge, UK, NewYork 2003
- Perrone MP , Cooper LN When networks disagree: ensemble methods for hybrid neural networks Mammone RJ Neural Networks for Speech and Image Processing Chapman-Hall 1993
- Bishop CM. Neural Networks for Pattern Recognition Oxford University Press 2005
- Zerpa LE , Queipo NV , Pintos S , Zerpa Salager JL An optimization methodology of alkaline-surfactant-polymer flooding processes using field scale numerical simulation and multiple surrogates Journal of Petroleum Science and Engineering 2005 47 3-4 197 208
- Goel T et al. Ensemble of surrogates Structural and Multidisciplinary Optimization 2007 33 3 199 216
- Acar E , Rais-Rohani M. Ensemble of metamodels with optimized weight factors Structural and Multidisciplinary Optimization 2009 37 3 279 94
- Chen S , Wang W , Zuylen H. Construct support vector machine ensemble to detect traffic incident Expert Systems with Applications 2009 36 8 10976 86
- Park , I. , and Grandhi , R.V. Quantifying Multiple Types of Uncertainty in Physics-based Simulation Using Bayesian Model Averaging AIAA Journal 49 5 2011 1038 1045