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Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 35, 2003 - Issue 3
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Articles

Constructing Meta-Models for Computer Experiments

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Pages 264-274 | Published online: 16 Feb 2018

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Yong Peng, Lin Hou, Quanwei Che, Ping Xu & Fan Li. (2019) Multi-objective robust optimization design of a front-end underframe structure for a high-speed train. Engineering Optimization 51:5, pages 753-774.
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RachelT. Silvestrini, DouglasC. Montgomery & Bradley Jones. (2013) Comparing Computer Experiments for the Gaussian Process Model Using Integrated Prediction Variance. Quality Engineering 25:2, pages 164-174.
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Rachel T. Johnson, Douglas C. Montgomery, Bradley Jones & Peter A. Parker. (2010) Comparing Computer Experiments for Fitting High-Order Polynomial Metamodels. Journal of Quality Technology 42:1, pages 86-102.
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Einat Neumann Ben-Ari & DavidM. Steinberg. (2007) Modeling Data from Computer Experiments: An Empirical Comparison of Kriging with MARS and Projection Pursuit Regression. Quality Engineering 19:4, pages 327-338.
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VictoriaC.P. Chen, Kwok-Leung Tsui, RussellR. Barton & Martin Meckesheimer. (2006) A review on design, modeling and applications of computer experiments. IIE Transactions 38:4, pages 273-291.
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David M Steinberg & Dizza Bursztyn. (2004) Data Analytic Tools for Understanding Random Field Regression Models. Technometrics 46:4, pages 411-420.
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H. Gao, L. Jézéque, E. Cabrol & B. Vitry. (2020) Robust Design of Suspension System with Polynomial Chaos Expansion and Machine Learning. Science & Technique 19:1, pages 43-54.
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Yue Zhang & Xiaofeng Li. (2019) Response-surface-model based on influencing factor analysis of subway tunnel temperature. Building and Environment 160, pages 106140.
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Shang-Ming Huang, Hsin-Ju Li, Yung-Chuan Liu, Chia-Hung Kuo & Chwen-Jen Shieh. (2017) An Efficient Approach for Lipase-Catalyzed Synthesis of Retinyl Laurate Nutraceutical by Combining Ultrasound Assistance and Artificial Neural Network Optimization. Molecules 22:11, pages 1972.
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Olumayowa T. Kajero, Tao Chen, Yuan Yao, Yao-Chen Chuang & David Shan Hill Wong. (2017) Meta-modelling in chemical process system engineering. Journal of the Taiwan Institute of Chemical Engineers 73, pages 135-145.
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V. I. Trushlyakov, V. Yu. Kudentsov, I. Yu. Lesnyak, K. A. Rozhaeva, S. A. Lavruk, M. M. Dron’ & K. I. Zharikov. (2017) Evaporation of a model liquid. Russian Engineering Research 37:1, pages 1-4.
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Nuno Ricardo Costa & João Lourenço. (2015) Gaussian Process Model – An Exploratory Study in the Response Surface Methodology. Quality and Reliability Engineering International 32:7, pages 2367-2380.
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Xingzhi Hu, Xiaoqian Chen, Geoffrey T. Parks & Wen Yao. (2016) Review of improved Monte Carlo methods in uncertainty-based design optimization for aerospace vehicles. Progress in Aerospace Sciences 86, pages 20-27.
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Akeem O. Arinkoola & David O. Ogbe. (2015) Examination of Experimental Designs and Response Surface Methods for Uncertainty Analysis of Production Forecast: A Niger Delta Case Study. Journal of Petroleum Engineering 2015, pages 1-16.
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Gabriella Dellino, Jack P. C. Kleijnen & Carlo Meloni. 2015. Uncertainty Management in Simulation-Optimization of Complex Systems. Uncertainty Management in Simulation-Optimization of Complex Systems 27 54 .
K.L. Tran, C. Douthe, K. Sab, J. Dallot & L. Davaine. (2014) A preliminary design formula for the strength of stiffened curved panels by design of experiment method. Thin-Walled Structures 79, pages 129-137.
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Xiong Shen, Guoqiang Zhang & Bjarne Bjerg. (2013) Assessments of experimental designs in response surface modelling process: Estimating ventilation rate in naturally ventilated livestock buildings. Energy and Buildings 62, pages 570-580.
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Rachel T. Johnson, Douglas C. Montgomery & Kathryn S. Kennedy. 2012. Frontiers in Statistical Quality Control 10. Frontiers in Statistical Quality Control 10 287 301 .
Theodore T. Allen & Shih‐Hsien Tseng. (2011) Variance plus bias optimal response surface designs with qualitative factors applied to stem choice modeling. Quality and Reliability Engineering International 27:8, pages 1199-1210.
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Sigal Levy & David M. Steinberg. (2011) Computer experiments: a review. AStA Advances in Statistical Analysis 94:4, pages 311-324.
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Russell R. Barton. (2009) Simulation optimization using metamodels. Simulation optimization using metamodels.
Bradley Jones & Rachel T. Johnson. (2009) Design and analysis for the Gaussian process model. Quality and Reliability Engineering International 25:5, pages 515-524.
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Rachel T. Johnson, Bradley Jones, John W. Fowler & Douglas C. Montgomery. (2008) Comparing designs for computer simulation experiments. Comparing designs for computer simulation experiments.
Isabel R. Santos & Pedro R. Santos. (2007) Simulation metamodels for modeling output distribution parameters. Simulation metamodels for modeling output distribution parameters.
Cristiano Cervellera, Aihong Wen & Victoria C.P. Chen. (2007) Neural network and regression spline value function approximations for stochastic dynamic programming. Computers & Operations Research 34:1, pages 70-90.
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Victor Oduguwa, Rajkumar Roy & Didier Farrugia. (2007) Development of a soft computing-based framework for engineering design optimisation with quantitative and qualitative search spaces. Applied Soft Computing 7:1, pages 166-188.
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Ron A. Bates, Ron S. Kenett, David M. Steinberg & Henry P. Wynn. (2016) Achieving Robust Design from Computer Simulations. Quality Technology & Quantitative Management 3:2, pages 161-177.
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Deng Huang & Theodore T. Allen. (2005) Design and Analysis of Variable Fidelity Experimentation Applied to Engine Valve Heat Treatment Process Design. Journal of the Royal Statistical Society Series C: Applied Statistics 54:2, pages 443-463.
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Longjun Liu. (2005) Could Enough Samples be more Important than Better Designs for Computer Experiments?. Could Enough Samples be more Important than Better Designs for Computer Experiments?.
Theodore T. Allen, Liyang Yu & John Schmitz. (2003) An Experimental Design Criterion for Minimizing Meta-Model Prediction Errors Applied to Die Casting Process Design. Journal of the Royal Statistical Society Series C: Applied Statistics 52:1, pages 103-117.
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