Zobrazeno 1 - 10
of 300
pro vyhledávání: '"A. Cannamela"'
Publikováno v:
International Journal for Uncertainty Quantification, 2024, 14 (1), pp.43-60
This paper deals with surrogate modelling of a computer code output in a hierarchical multi-fidelity context, i.e., when the output can be evaluated at different levels of accuracy and computational cost. Using observations of the output at low- and
Externí odkaz:
http://arxiv.org/abs/2312.02575
Autor:
Johansen, C., Mejia, V., Scrushy, M., Tiziani, S., Cannamela, P., Wan, B., Dultz, L.A., Cripps, M.W., Sanders, D., Starr, A., Grant, J., Park, C.
Publikováno v:
In Injury November 2024 55(11)
Publikováno v:
14th World Congress in Computational Mechanics and ECCOMAS Congress 2020 (WCCM-ECCOMAS), Jan 2021, Virtual conference, originally scheduled in Paris, France
Numerical models based on partial differential equations (PDE), or integro-differential equations, are ubiquitous in engineering and science, making it possible to understand or design systems for which physical experiments would be expensive-sometim
Externí odkaz:
http://arxiv.org/abs/2103.14559
Autor:
Cannamela, Danila1 dcanname@colby.edu
Publikováno v:
Italianist. Jun2023, Vol. 43 Issue 2, p341-360. 20p.
Autor:
Pignatti, Marco, Pinto, Valentina, Miralles, Maria Elisa Lozano, Giorgini, Federico A., Cannamela, Giacomo, Cipriani, Riccardo
Publikováno v:
In Journal of Plastic, Reconstructive & Aesthetic Surgery July 2020 73(7):1348-1356
Akademický článek
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Complex computer codes are widely used in science and engineering to model physical phenomena. Furthermore, it is common that they have a large number of input parameters. Global sensitivity analysis aims to identify those which have the most importa
Externí odkaz:
http://arxiv.org/abs/1307.2223
Autor:
Gratiet, Loic Le, Cannamela, Claire
Kriging-based surrogate models have become very popular during the last decades to approximate a computer code output from few simulations. In practical applications, it is very common to sequentially add new simulations to obtain more accurate appro
Externí odkaz:
http://arxiv.org/abs/1210.6187
Autor:
Olstad, K. †, Shea, K.G. ‡, Cannamela, P.C. ‡, Polousky, J.D. §, Ekman, S. ‖, Ytrehus, B. ¶, Carlson, C.S. #
Publikováno v:
In Osteoarthritis and Cartilage December 2018 26(12):1691-1698
Publikováno v:
Annals of Applied Statistics 2008, Vol. 2, No. 4, 1554-1580
In this paper we propose and discuss variance reduction techniques for the estimation of quantiles of the output of a complex model with random input parameters. These techniques are based on the use of a reduced model, such as a metamodel or a respo
Externí odkaz:
http://arxiv.org/abs/0802.2426