دانلود مقاله ISI انگلیسی شماره 100553
ترجمه فارسی عنوان مقاله

روند چندجمله ای درهم و برهمی برای بهبود پیش بینی کننده های مبتنی بر فرآیند گاوسی

عنوان انگلیسی
Nested polynomial trends for the improvement of Gaussian process-based predictors
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
100553 2017 14 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Computational Physics, Volume 346, 1 October 2017, Pages 389-402

ترجمه کلمات کلیدی
آزمایش کامپیوتری، روند گاوسی، روند چندجملهای پوشیده شده، چارچوب بیزی،
کلمات کلیدی انگلیسی
Computer experiment; Gaussian process; Nested polynomial trend; Bayesian framework;
پیش نمایش مقاله
پیش نمایش مقاله  روند چندجمله ای درهم و برهمی برای بهبود پیش بینی کننده های مبتنی بر فرآیند گاوسی

چکیده انگلیسی

The role of simulation keeps increasing for the sensitivity analysis and the uncertainty quantification of complex systems. Such numerical procedures are generally based on the processing of a huge amount of code evaluations. When the computational cost associated with one particular evaluation of the code is high, such direct approaches based on the computer code only, are not affordable. Surrogate models have therefore to be introduced to interpolate the information given by a fixed set of code evaluations to the whole input space. When confronted to deterministic mappings, the Gaussian process regression (GPR), or kriging, presents a good compromise between complexity, efficiency and error control. Such a method considers the quantity of interest of the system as a particular realization of a Gaussian stochastic process, whose mean and covariance functions have to be identified from the available code evaluations. In this context, this work proposes an innovative parametrization of this mean function, which is based on the composition of two polynomials. This approach is particularly relevant for the approximation of strongly non linear quantities of interest from very little information. After presenting the theoretical basis of this method, this work compares its efficiency to alternative approaches on a series of examples.