Results 11 to 20 of about 3,769,150 (256)
Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity
International Journal for Uncertainty Quantification, 2014 International audienceWe consider in this paper the problem of building a fast-running approximation—also called surrogate model—of acomplex computer code.
Le Gratiet, Loic, Garnier, Josselin
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Co-kriging when the soil and ancillary data are not co-located
, 2003 Data such as digitized aerial photographs, electrical conductivity and yield are intensive and relatively inexpensive to obtain compared with collecting soil data by sampling.
Kerry, R., Oliver, M. A.
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Multi-fidelity modelling via recursive co-kriging and Gaussian-Markov random fields. [PDF]
Proc Math Phys Eng Sci, 2015 We propose a new framework for design under uncertainty based on stochastic computer simulations and multi-level recursive co-kriging. The proposed methodology simultaneously takes into account multi-fidelity in models, such as direct numerical simulations versus empirical formulae, as well as multi-fidelity in the probability space (e.g.
Perdikaris P +3 more
europepmc +5 more sources
The Many Forms of Co-kriging: A Diversity of Multivariate Spatial Estimators
Mathematical Geosciences, 2023 AbstractIn this expository review paper, we show that co-kriging, a widely used geostatistical multivariate optimal linear estimator, has a diverse range of extensions that we have collected and illustrated to show the potential of this spatial interpolator.
Peter A. Dowd, Eulogio Pardo-Igúzquiza
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Hungarian Geographical Bulletin, 2021 The relationship between precipitation and elevation is a well-known topic in the field of geography and meteorology. Radar-based precipitation data are often used in hydrologic models, however, they have several inaccuracies, and elevation can be one of
Tamás Schneck +2 more
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Cold Season’s Air Temperature Geostatistical Modeling: Considering the Landsat Thermal Band and Snow Cover Area [PDF]
جغرافیا و مخاطرات محیطی, 2018 Providing climatic data like temperature in good spatial resolution is a key requirement for many geographical, ecological and bioclimatic research. With this in mind, various related studies use thermal remote sensing images as auxiliary data to enhance
مسعود مینائی
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Estimating precipitation intensity and its spatial distribution based on fractal theory (Case study: Tireh-Borujerd watershed) [PDF]
مدلسازی و مدیریت آب و خاک, 2023 Introduction Estimating the amount and intensity of precipitation and its spatial distribution in various return periods is necessary for flood estimation hydrological models.
Tayebeh Sepahvabd +3 more
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Investigating the spatial pattern of total selenium concentration in soil surface in Central Iran (case study: Isfahan Province) [PDF]
علوم محیطی, 2020 Introduction: The study of the spatial distribution of heavy metals is very important in land management and planning. The geostatistics theory is used to estimate spatial variables in unmeasured points.
Somayeh Sadr, Zahra Movahedi Rad
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High anisotropy space exploration with co-Kriging method [PDF]
AIP Conference Proceedings, 2019 For a black box data-space exploration, classical DoE method prescribes a cluster of quasi-isotropic design points following a certain space-infill criterion, however the objective function behaves. Adding new points often disturbs the original spatial-infill properties, which restricts dimension-augmentation and reusability of data.
Zebin Zhang +2 more
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Sensors, 2017 In the practice of interpolating near-surface soil moisture measured by a wireless sensor network (WSN) grid, traditional Kriging methods with auxiliary variables, such as Co-kriging and Kriging with external drift (KED), cannot achieve satisfactory ...
Jialin Zhang +5 more
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