Reliable low-cost co-kriging modeling of microwave devices [PDF]
2012 IEEE/MTT-S International Microwave Symposium Digest, 2012 A reliable methodology for accurate modeling of microwave devices is presented. Our approach exploits co-kriging which utilizes low- and high-fidelity EM simulation data and combines them into a single surrogate model. Densely sampled low-fidelity data determines a trend function which is further corrected by sparsely sampled high-fidelity simulations.
Koziel, Slawomir +2 more
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Variable-Fidelity Electromagnetic Simulations and Co-Kriging for Accurate Modeling of Antennas [PDF]
IEEE Transactions on Antennas and Propagation, 2013 Accurate and fast models are indispensable in contemporary antenna design. In this paper, we describe the low-cost antenna modeling methodology involving variable-fidelity electromagnetic (EM) simulations and co-Kriging. Our approach exploits sparsely sampled accurate (high-fidelity) EM data as well as densely sampled coarse-discretization (low ...
Koziel, S +3 more
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A Probability Co-Kriging Model to Account for Reporting Bias and Recognize Areas at High Risk for Zebra Mussels and Eurasian Watermilfoil Invasions in Minnesota [PDF]
Frontiers in Veterinary Science, 2018 Zebra mussels (ZMs) (Dreissena polymorpha) and Eurasian watermilfoil (EWM) (Myriophyllum spicatum) are aggressive aquatic invasive species posing a conservation burden on Minnesota.
Kaushi S. T. Kanankege +7 more
doaj +2 more sources
Efficient simulation-driven design optimization of antennas using co-kriging [PDF]
Proceedings of the 2012 IEEE International Symposium on Antennas and Propagation, 2012 We present an efficient technique for design optimization of antenna structures. Our approach exploits coarse-discretization electromagnetic (EM) simulations of the antenna of interest that are used to create its fast initial model (a surrogate) through kriging.
Koziel, Slawomir +3 more
openaire +4 more sources
A generative deep neural network as an alternative to co-kriging
Applied Computing and GeosciencesIn geosciences, kriging is leading spatial interpolation, and co-kriging is the most commonly used method for accomplishing spatial interpolation of a target variable by incorporating information from a secondary variable.
Herbert Rakotonirina +3 more
doaj +3 more sources
Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging [PDF]
IEEE Access, 2020 Utilization of fast surrogate models has become a viable alternative to direct handling of full-wave electromagnetic (EM) simulations in EM-driven design.
Anna Pietrenko-Dabrowska +1 more
doaj +3 more sources
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
Multi-fidelity wake modelling based on Co-Kriging method [PDF]
Journal of Physics: Conference Series, 2016 The article presents an approach to combine wake models of multiple levels of fidelity, which is capable of giving accurate predictions with only a small number of high fidelity samples. The G. C. Larsen and k-e-fP based RANS models are adopted as ensemble members of low fidelity and high fidelity models, respectively.
Wang, Y. M. +5 more
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Mapping forest aboveground carbon stock of combined stratified sampling and RFRK model with mean annual temperature and precipitation [PDF]
Scientific ReportsAccurately estimating forest aboveground carbon stock (ACS) is essential for achieving carbon neutrality. At present, most non-parametric models still have errors in estimating carbon stock in regions.
Min Peng +5 more
doaj +2 more sources
Spatial mapping of soil chemical properties using multivariate geostatistics. A study from cropland in eastern Croatia [PDF]
Journal of Central European Agriculture, 2021 The spatial variability of soil chemical properties is affected by factors of soil formation and human activities. Understanding their spatial variability will improve agricultural production, reduce environmental problems (e.g., soil pollution, offsite ...
Igor Bogunovic +3 more
doaj +1 more source