Results 181 to 190 of about 10,081 (210)
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Empirical Kriging models and their applications to QSAR
Journal of Chemometrics, 2007AbstractA general Kriging model consists of two additive components: a parametric term and a stochastic error process. It is known that Kriging is an interpolating predictor and allows for a better fit to the data, but suffers from a decreasing ability to generalize to unseen data.
Hong Yin +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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Modelling Rainfall Data Using a Bayesian Kriged-Kalman Model [PDF]
, 2006 A suitable model for analyzing rainfall data needs to take into account variation in both space and time. The method of kriging is a popular approach in spatial statistics which makes predictions for spatial data. Kalman filtering using dynamic models is often used to analyze temporal data.
SAHU S. K +2 more
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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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Limit kriging in finite element environmental modeling
2011Finite element method is used as a basis for an environmental model of an artificial water reservoir (lake) Botonega in Croatia. Geometry of the model has to be produced from geodesic data of the lake. Due to presence of the water available data are very limited and not even a simple finite element model could be made.
Kožar, Ivica +2 more
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Linear Models for Spatial Data: Kriging
1991Just as data collected sequentially in time may be correlated, data collected at known locations in space may be correlated. For example, deposits of high-quality copper are more likely to occur near other high-quality deposits. The levels of lead contamination in the soil around a smelter are likely to be correlated.
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A Generalized Hierarchical Co-Kriging Model for Multi-Fidelity Data Fusion
Structural and Multidisciplinary Optimization, 2020Peng Jin, Zhendong Guo, Qi Zhou
exaly
Enhanced Kriging Leave-One-Out Cross-Validation in Improving Model Estimation and Optimization
Computer Methods in Applied Mechanics and Engineering, 2023Xueguan Song, Xiaonan Lai, Pengwei Liang
exaly