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ooDACE toolbox: a flexible object-oriented Kriging implementation

Ivo Couckuyt (UGent) , Tom Dhaene (UGent) and Piet Demeester (UGent)
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Abstract
When analyzing data from computationally expensive simulation codes, surrogate modeling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualization and optimization. Kriging is a popular surrogate modeling technique used for the Design and Analysis of Computer Experiments (DACE). Hence, the past decade Kriging has been the subject of extensive research and many extensions have been proposed, e.g., co-Kriging, stochastic Kriging, blind Kriging, etc. However, few Kriging implementations are publicly available and tailored towards scientists and engineers. Furthermore, no Kriging toolbox exists that unifies several Kriging flavors. This paper addresses this need by presenting an efficient object-oriented Kriging implementation and several Kriging extensions, providing a flexible and easily extendable framework to test and implement new Kriging flavors while reusing as much code as possible.
Keywords
DESIGN, IBCN, Kriging, surrogate modeling, Gaussian process, co-Kriging, blind Kriging, metamodeling, DACE

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Please use this url to cite or link to this publication:

MLA
Couckuyt, Ivo, Tom Dhaene, and Piet Demeester. “ooDACE Toolbox: a Flexible Object-oriented Kriging Implementation.” JOURNAL OF MACHINE LEARNING RESEARCH 15 (2014): 3183–3186. Print.
APA
Couckuyt, I., Dhaene, T., & Demeester, P. (2014). ooDACE toolbox: a flexible object-oriented Kriging implementation. JOURNAL OF MACHINE LEARNING RESEARCH, 15, 3183–3186.
Chicago author-date
Couckuyt, Ivo, Tom Dhaene, and Piet Demeester. 2014. “ooDACE Toolbox: a Flexible Object-oriented Kriging Implementation.” Journal of Machine Learning Research 15: 3183–3186.
Chicago author-date (all authors)
Couckuyt, Ivo, Tom Dhaene, and Piet Demeester. 2014. “ooDACE Toolbox: a Flexible Object-oriented Kriging Implementation.” Journal of Machine Learning Research 15: 3183–3186.
Vancouver
1.
Couckuyt I, Dhaene T, Demeester P. ooDACE toolbox: a flexible object-oriented Kriging implementation. JOURNAL OF MACHINE LEARNING RESEARCH. 2014;15:3183–6.
IEEE
[1]
I. Couckuyt, T. Dhaene, and P. Demeester, “ooDACE toolbox: a flexible object-oriented Kriging implementation,” JOURNAL OF MACHINE LEARNING RESEARCH, vol. 15, pp. 3183–3186, 2014.
@article{6915561,
  abstract     = {When analyzing data from computationally expensive simulation codes, surrogate modeling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualization and optimization. Kriging is a popular surrogate modeling technique used for the Design and Analysis of Computer Experiments (DACE). Hence, the past decade Kriging has been the subject of extensive research and many extensions have been proposed, e.g., co-Kriging, stochastic Kriging, blind Kriging, etc. However, few Kriging implementations are publicly available and tailored towards scientists and engineers. Furthermore, no Kriging toolbox exists that unifies several Kriging flavors. This paper addresses this need by presenting an efficient object-oriented Kriging implementation and several Kriging extensions, providing a flexible and easily extendable framework to test and implement new Kriging flavors while reusing as much code as possible.},
  author       = {Couckuyt, Ivo and Dhaene, Tom and Demeester, Piet},
  issn         = {1532-4435},
  journal      = {JOURNAL OF MACHINE LEARNING RESEARCH},
  keywords     = {DESIGN,IBCN,Kriging,surrogate modeling,Gaussian process,co-Kriging,blind Kriging,metamodeling,DACE},
  language     = {eng},
  pages        = {3183--3186},
  title        = {ooDACE toolbox: a flexible object-oriented Kriging implementation},
  volume       = {15},
  year         = {2014},
}

Web of Science
Times cited: