Results 21 to 30 of about 14,433 (200)

Function-on-Function Kriging, With Applications to Three-Dimensional Printing of Aortic Tissues [PDF]

open access: yesTechnometrics, 2020
3D-printed medical prototypes, which use synthetic metamaterials to mimic biological tissue, are becoming increasingly important in urgent surgical applications. However, the mimicking of tissue mechanical properties via 3D-printed metamaterial can be difficult and time-consuming, due to the functional nature of both inputs (metamaterial structure) and
Jialei Chen 0002   +3 more
openaire   +3 more sources

Separation Reliability Analysis for the Low-Shock Separation Nut with Mechanism Motion Failure Mode

open access: yesAerospace, 2022
A functional reliability simulation method based on the Kriging model is proposed to efficiently evaluate the functional reliability of low-shock separation nuts.
Lei Niu   +3 more
doaj   +1 more source

Sliced Gradient-Enhanced Kriging for High-Dimensional Function Approximation [PDF]

open access: yesSIAM Journal on Scientific Computing, 2023
Gradient-enhanced Kriging (GE-Kriging) is a well-established surrogate modelling technique for approximating expensive computational models. However, it tends to get impractical for high-dimensional problems due to the size of the inherent correlation matrix and the associated high-dimensional hyper-parameter tuning problem.
Kai Cheng, Ralf Zimmermann 0002
openaire   +4 more sources

Kriging with Nonparametric Variance Function Estimation [PDF]

open access: yesBiometrics, 1999
Summary. A method for fitting regression models to data that exhibit spatial correlation and heteroskedas‐ticity is proposed. It is well known that ignoring a nonconstant variance does not bias least‐squares estimates of regression parameters; thus, data analysts are easily lead to the false belief that moderate heteroskedas‐ticity can generally be ...
Opsomer, Jean   +4 more
openaire   +5 more sources

Functional Kriging for Spatiotemporal Modeling of Nitrogen Dioxide in a Middle Eastern Megacity

open access: yesAtmosphere, 2022
Long-term hour-specific air pollution exposure estimates have rarely been of interest in epidemiological research. However, this can be relevant for studies that aim to estimate the residential exposure for the hours that subjects mostly spend time there,
Elham Ahmadi Basiri   +3 more
doaj   +1 more source

Intrinsic random functions and universal kriging on the circle [PDF]

open access: yesStatistics & Probability Letters, 2016
14 pages, initial ...
Chunfeng Huang   +2 more
openaire   +2 more sources

Anomaly detection in geostatistical models with application to groundwater level data in the Gaza Coastal Aquifer [PDF]

open access: yesSongklanakarin Journal of Science and Technology (SJST), 2022
In geostatistics, the detection of anomalous observations has a particular importance because of the changes they can create in environmental and geological patterns. Few methods for detecting such observations in univariate data have been proposed for
Ali H. Abuzaid   +2 more
doaj   +1 more source

D-STEM v2: A Software for Modeling Functional Spatio-Temporal Data

open access: yesJournal of Statistical Software, 2021
Functional spatio-temporal data naturally arise in many environmental and climate applications where data are collected in a three-dimensional space over time.
Yaqiong Wang   +2 more
doaj   +1 more source

Prediction of spatial distribution characteristics of ecosystem functions based on a minimum data set of functional traits of desert plants

open access: yesFrontiers in Plant Science, 2023
The relationship between plant functional traits and ecosystem function is a hot topic in current ecological research, and community-level traits based on individual plant functional traits play important roles in ecosystem function.
Yudong Chen   +20 more
doaj   +1 more source

Parameter Analysis and Optimization of Annular Jet Pump Based on Kriging Model

open access: yesApplied Sciences, 2020
Jet pump efficiency heavily relies on the geometrical parameters of the pump design and parameter global optimization in the full variable space is still a big challenge.
Kai Xu   +6 more
doaj   +1 more source

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