Results 171 to 180 of about 14,309 (209)

Accelerating SCF Orbital Optimization with S-GEK/RVO: Efficient Subspace Compression and Robust Convergence. [PDF]

J Chem Theory Comput
Fdez Galván I, Weßling D, Lindh R.
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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
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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
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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
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A universal kriging approach for spatial functional data

Stochastic Environmental Research and Risk Assessment, 2013
In a wide range of scientific fields the outputs coming from certain measurements often come in form of curves. In this paper we give a solution to the problem of spatial prediction of non-stationary functional data. We propose a new predictor by extending the classical universal kriging predictor for univariate data to the context of functional data ...
William Caballero, Ramón Giraldo, Jorge Mateu   +2 more
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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.
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Frequency response function-based model updating using Kriging model

Mechanical Systems and Signal Processing, 2017
Abstract An acceleration frequency response function (FRF) based model updating method is presented in this paper, which introduces Kriging model as metamodel into the optimization process instead of iterating the finite element analysis directly.
J.T. Wang, C.J. Wang, J.P. Zhao
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Functional Decomposition Kriging for Embedding Stochastic Anisotropy Simulations

2017
Functional analysis of the kriging algorithm is accomplished with consecutive projections of vectors in Hilbert space. The innovation unveils “functional decomposition kriging” (FDK), which can forecast fields on spatially continuous domains without using blocks, cells, or elements.
J. A. Vargas-Guzmán, B. Vargas-Murillo
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Global 3D ionospheric shape function modeling with kriging

Journal of Geodesy
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Haixia Lyu, Manuel Hernández-Pajares, Min Li, Enric Monte-Moreno, Fabricio S. Prol, Hongping Zhang, Chenlong Deng, Jingnan Liu   +7 more
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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.
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