Results 71 to 80 of about 14,433 (200)
Residual Kriging for Functional Spatial Prediction of Salinity Curves [PDF]
Recently, several methodologies to perform geostatistical analysis of functional data have been proposed. All of them assume that the spatial functional process considered is stationary. However, in practice, we often have nonstationary functional data because there exists an explicit spatial trend in the mean.
Adriana Reyes +2 more
openaire +1 more source
Abstract Vegetation indices (VIs), such as normalized difference vegetation index (NDVI), are widely used to assess nitrogen (N) status in crop systems and are gaining interest in turfgrass management. However, most studies have been conducted in controlled settings, and their relevance under real‐world golf course conditions remains unclear.
Madan Sapkota +7 more
wiley +1 more source
Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
wiley +1 more source
ABSTRACT Addressing ongoing calls for a more robust understanding of philanthropic foundations, this paper uses metaphor analysis to map and analyse analogical metaphors on foundations—metaphors that make a direct comparison between philanthropic foundations and another domain—put forward in academic and non‐academic discourse.
Tobias Jung
wiley +1 more source
Experiment / simulation integrated shape optimization using variable fidelity Kriging model approach
An attempt of experiment / simulation integrated design optimization is performed for the blade airfoil shape of a vertical axis wind turbine. A variable fidelity Kriging surrogate model approach is utilized in this integrated design optimization, in ...
Wataru YAMAZAKI
doaj +1 more source
Abstract Large‐scale groundwater quality prediction is often constrained by sparse sampling, limiting the reliability of spatial assessments. This study introduces Tabular Prior‐data Fitted Network (TabPFN), a machine learning model based on prior‐fitting networks, to address this challenge and enable high‐precision mapping of groundwater bicarbonate ...
Tong Sun +8 more
wiley +1 more source
Polynomial-Chaos-based Kriging
Computer simulation has become the standard tool in many engineering fields for designing and optimizing systems, as well as for assessing their reliability.
Schoebi, R., Sudret, B., Wiart, J.
core +1 more source
Abstract INTRODUCTION Alzheimer's disease and related dementias are influenced by genetic and environmental risk factors. We investigated the relationship between contextual exposures and cognitive outcomes, independent of and in interaction with polygenic risk.
Diane Xue +6 more
wiley +1 more source
Kriging for functional data: uncertainty assessment [PDF]
We predict a curve at an unmonitored site taking into account exogenous variables using a functional kriging model with external drift and, alternatively, an additive model with a spatio-temporal smooth term. To evaluate uncertainty of the predicted curves, a semi-parametric bootstrap approach is used for the first, while standard inference is used for
IGNACCOLO, Rosaria +1 more
openaire
A Guide to Bayesian Optimization in Bioprocess Engineering
ABSTRACT Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small data sets, and provide adaptive suggestions for sequential experimentation.
Maximilian Siska +5 more
wiley +1 more source

