Results 201 to 210 of about 9,630 (234)
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A Non-Homogeneous Model for Kriging Dosimetric Data
Mathematical Geosciences, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lajaunie, Christian +4 more
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A kriging approach to the analysis of climate model experiments
Journal of Agricultural, Biological, and Environmental Statistics, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Surrogate modeling of microwave structures using kriging, co‐kriging, and space mapping
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 2012SUMMARYSpace mapping (SM) is one of the most popular techniques for creating computationally cheap and reasonably accurate surrogates of electromagnetic‐simulated microwave structures (so‐called fine models) using underlying coarse models, typically equivalent circuits.
Ivo Couckuyt +2 more
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Kriging and moving window kriging on a sphere in geometric (GNSS/levelling) geoid modelling
Survey Review, 2016A comparison of kriging and moving window kriging (MWK) on a sphere is performed on GNSS/levelling data.
M. Ligas, M. Kulczycki
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A kriging interpolation model for geographical flows
International Journal of Geographical Information Science, 2023Ya Fang +6 more
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Model Reduction by PCA and Kriging
2018info:eu-repo/semantics ...
Aversano, Gianmarco +3 more
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Factorial kriging for multiscale modelling
2014SYNOPSIS This paper presents a matrix formulation of factorial kriging, and its relationships with simple and ordinary kriging. Similar to other kriging methods, factorial kriging can be applied to both stationary and intrinsic stochastic processes, and is often used as a local operator.
Ma, Y. Z. +4 more
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Modeling Cloud performance with Kriging
2012 34th International Conference on Software Engineering (ICSE), 2012Alessio Gambi, Giovanni Toffetti
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On Using Kriging Models for Complex Design
Volume 5: 37th Design Automation Conference, Parts A and B, 2011The design of most modern systems requires the tight integration of multiple disciplines. In practice, these multiple disciplines are often optimized independently, given only fixed values or targets for their interactions with other disciplines. The result is a system that may not represent the optimal system-level design.
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Conformal Prediction for Functional Kriging Models
2023In this work we introduce a conformal prediction method for functional kriging. Conformal Prediction (CP) is a framework in machine learning and statistical inference that provides a principled way to quantify uncertainty and make predictions without relying on specific distributional assumptions.
Diana A., Romano E., Adzic J.
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