KrigingPrincipal component analysisIn this work, we propose an Inverse Uncertainty Quantification (IUQ) approach to assigning Probability Density Functions (PDFs) to uncertain input parameters of Thermal-Hydraulic (T-H) models used to assess the reliability of passive safety systems. The approach uses...
(2010) call this strategy Kriging Believer. However, they found that when the GP predicts expectations below the currently seen minimum, gˆ, this strategy can lead to the batch clustering around the same query point. To avoid this, they tried another strategy, Constant Liar, where they use...
The Bayesian analysis also shows that the estimated uncertainty is significantly reduced when more information is used (for the 100 year return period, the 90% credible intervals range reduces from 140% to 31% of the corresponding flood peak estimate). Further analyses show that the sensitivity ...
Various types of kriging models are used in hydrology, such as ordinary kriging (Adhikary et al.2016; Farmer2016), canonical kriging or co-kriging (Ouarda et al.2001; Chokmani and Ouarda2004), topological kriging or ‘top-kriging’ (Skøien et al.2006; Skøien and Blöschl2007; Persi...
70. Mohammed Awadallah, Ameen El-Sinawi.2020.Effect and detection of cracks on small wind turbine blade vibration using special Kriging analysis of spectral shifts, Measurement, volume 151, 107076, ISSN 0263–2241, https://doi.org/10.1016/j.measurement.2019.107076 71. Ahmed Ali Farhan Ogaili, Al...
This technique is particularly useful when datasets are too small to utilize more complex interpolation methods (that is, kriging, spline or multiple regression techniques)48. However, IDW is sensitive to site clustering and is optimized when samples are evenly spaced. Therefore, in locations with ...
Standard error estimates from the CenTrends estimation process (kriging) indicates reasonable accuracies back to the 1950s. The same station data have been used in the 1981–2014 CHIRPS version 2 and CenTrends version 1.0 datasets; the correlation between the October-September southeastern Ethiopia ...
Description: The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Proces...
Paying particular attention to data assimilation, we review linkages to optimal interpolation, kriging, Kalman filtering, smoothing, and variational analysis. Discussion is provided concerning Monte Carlo methods for implementing Bayesian analysis, including importance sampling, particle filtering, ensemble ...
The reliability analysis system is currently evolving, and reliability analysis efforts are also focusing more on correctness and efficiency. The effectiveness of the active learning Kriging metamodel for the investigation of structural system reliability has been demonstrated. In order to effectively predic...