Results 171 to 180 of about 14,433 (200)

Conformal Based Uncertainty Bands for Predictions in Functional Ordinary Kriging

Functional Ordinary Kriging is the most widley used method to predict a curve at a given spatial point by computing a weighted average of observed functional values in space. Determining the uncertainty associated with predicted curves remains a challenge.
Elvira Romano
exaly   +3 more sources

Kriging-based optimization of functionally graded structures

Structural and Multidisciplinary Optimization, 2021
This work presents an efficient methodology for the optimum design of functionally graded structures using a Kriging-based approach. The method combines an adaptive Kriging framework with a hybrid particle swarm optimization (PSO) algorithm to improve the computational efficiency of the optimization process.
Marina Alves Maia, Evandro Parente, Antônio Macário Cartaxo de Melo   +2 more
openaire   +1 more source

A novel learning function based on Kriging for reliability analysis

Reliability Engineering & System Safety, 2020
Abstract Adaptively constructing the surrogate model for reliability analysis has been widely studied for the advantage of guaranteeing the estimation accuracy while calling the real performance function as little as possible. A new learning function called Folded Normal based Expected Improvement Function (FNEIF) is proposed to efficiently estimate ...
Yan Shi 0014, Zhenzhou Lu, Ruyang He, Yicheng Zhou, Siyu Chen   +4 more
openaire   +1 more source

Conditional optimization of a noisy function using a kriging metamodel

Journal of Global Optimization, 2019
The efficient global optimization method is popular for the global optimization of computer-intensive black-box functions. Extensions exist, either for the optimization of noisy functions, or for the conditional optimization of deterministic functions, i.e.
Diariétou Sambakhé, Lauriane Rouan, Jean-Noël Bacro, Eric Gozé   +3 more
openaire   +3 more sources

Kriging with Nonparametric Variance Function Estimation

1998
A method for fitting regression models to data that exhibit spatial correlation and Heteroskedasticity is proposed. A combination of parametric and nonparametric regression techniques is used to iteratively estimate the various components of the model. The approach is demonstrated on a large dataset of predicted nitrogen runoff from agricultural lands ...
Opsomer, Jean D., Ruppert, D., Wand, M.P., Holst, U., Hossjer, O., Opsomer, Jean D., Ruppert, D., Wand, M.P., Holst, U., Hossjer, O.   +9 more
openaire   +1 more source

The equivalence of predictions from universal kriging and intrinsic random-function kriging

Mathematical Geology, 1990
A proof is provided that the predictions obtained from kriging based on intrinsic random functions of orderk are identical to those obtained from anappropriate universal kriging model. This is a theoretical result based on known variability measures. It does not imply that people performing traditional universal kriging will get the same predictions as
openaire   +1 more source

Conformal Prediction for Functional Kriging Models

2023
In 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.
openaire   +1 more source

AN ENHANCEMENT OF FINITE ELEMENT METHOD WITH MOVING KRIGING SHAPE FUNCTIONS

International Journal of Computational Methods, 2005
This paper presents an enhancement of the finite element method (FEM) by adopting the moving Kriging (MK) interpolation as a substitute for the traditional hat functions. The MK shape functions can be referred as element-free because their construction is not tied to the element geometry. Kriging interpolation is a geostatistical technique for spatial
Plengkhom, K., Kanok-Nukulchai, W.
openaire   +1 more source

A regularization method for constructing trend function in Kriging model

Structural and Multidisciplinary Optimization, 2018
Kriging is a popular surrogate for approximating computationally expensive computer experiments. When sample points are limited, it is difficult to identify the overall trend of the problem at hand properly. Thanks to the interpolating characteristic of the Kriging model, a constant is widely used as the trend function, which neglects the overall trend
Yi Zhang, Wen Yao, Siyu Ye, Xiaoqian Chen   +3 more
openaire   +1 more source

Interval-valued random functions and the kriging of intervals

Mathematical Geology, 1988
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources