Spatiotemporal reconstructions of global CO 2 ‐fluxes using Gaussian Markov random fields
Sign Up to like & getrecommendations! Published in 2019 at "Environmetrics"
DOI: 10.1002/env.2610
Abstract: Atmospheric inverse modeling is a method for reconstructing historical fluxes of green‐house gas between land and atmosphere, using observed atmospheric concentrations and an atmospheric tracer transport model. The small number of observed atmospheric concentrations in… read more here.
Keywords: fluxes using; random fields; markov random; using gaussian ... See more keywords
Random fields on the hypertorus: Covariance modeling and applications
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DOI: 10.1002/env.2701
Abstract: This article gives a comprehensive theoretical framework to the modeling, inference, and applications of Gaussian random fields using what we term the hypertorus as an index set. The hypertorus is obtained through a product of… read more here.
Keywords: hypertorus covariance; random fields; seasonality; covariance ... See more keywords
Influence of stochastic geometric imperfections on the load-carrying behaviour of thin-walled structures using constrained random fields
Sign Up to like & getrecommendations! Published in 2018 at "Computational Mechanics"
DOI: 10.1007/s00466-018-1554-0
Abstract: Since structural engineering requires highly developed and optimized structures, the thickness dependency is one of the most controversially debated topics. This paper deals with stability analysis of lightweight thin structures combined with arbitrary geometrical imperfections.… read more here.
Keywords: random fields; constrained random; geometric imperfections; random ... See more keywords
On a continuous spectral algorithm for simulating non-stationary Gaussian random fields
Sign Up to like & getrecommendations! Published in 2017 at "Stochastic Environmental Research and Risk Assessment"
DOI: 10.1007/s00477-017-1402-3
Abstract: This paper presents an algorithm for simulating Gaussian random fields with zero mean and non-stationary covariance functions. The simulated field is obtained as a weighted sum of cosine waves with random frequencies and random phases,… read more here.
Keywords: random fields; stationary gaussian; algorithm simulating; non stationary ... See more keywords
Probabilistic modeling of shallow landslide initiation using regional scale random fields
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DOI: 10.1007/s10346-020-01438-y
Abstract: Regional mapping of landslide susceptibility aims to identify zones of potential instability across geological settings. Given their predictive capabilities, physically based, deterministic models are useful tools for landslide triggering studies at regional scale. However, they… read more here.
Keywords: random fields; scale random; landslide susceptibility; scale ... See more keywords
Reduction Principle for Functionals of Vector Random Fields
Sign Up to like & getrecommendations! Published in 2019 at "Methodology and Computing in Applied Probability"
DOI: 10.1007/s11009-019-09720-w
Abstract: We prove a version of the reduction principle for functionals of vector long-range dependent random fields. The components of the fields may have different long-range dependent behaviours. The results are illustrated by an application to… read more here.
Keywords: functionals vector; random fields; reduction principle; principle functionals ... See more keywords
An Explicit Solution for Image Restoration using Markov Random Fields
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Signal Processing Systems"
DOI: 10.1007/s11265-019-01470-9
Abstract: Image restoration and denoising is an essential preprocessing step for almost every subsequent task in computer vision. Markov Random Fields offer a well-founded, sophisticated approach for this purpose, but unfortunately the associated computation procedures are… read more here.
Keywords: random fields; image restoration; markov random;
Kernel regression estimation with errors-in-variables for random fields
Sign Up to like & getrecommendations! Published in 2019 at "Afrika Matematika"
DOI: 10.1007/s13370-019-00654-7
Abstract: In this paper, we investigate kernel regression estimation when the data are contaminated by measurement errors in the context of random fields. We establish sharp rate of weak and strong convergence of the kernel regression… read more here.
Keywords: regression; random fields; kernel regression; regression estimation ... See more keywords
Structural vibration analysis with random fields using the hierarchical finite element method
Sign Up to like & getrecommendations! Published in 2019 at "Journal of the Brazilian Society of Mechanical Sciences and Engineering"
DOI: 10.1007/s40430-019-1579-0
Abstract: Element-based techniques, like the finite element method, are the standard approach in industry for low-frequency applications in structural dynamics. However, mesh requirements can significantly increase the computational cost for increasing frequencies. In addition, randomness in… read more here.
Keywords: random fields; hierarchical finite; finite element; element ... See more keywords
Stepwise covariance matrix decomposition for efficient simulation of multivariate large-scale three-dimensional random fields
Sign Up to like & getrecommendations! Published in 2019 at "Applied Mathematical Modelling"
DOI: 10.1016/j.apm.2018.11.011
Abstract: Abstract The spatial variability of geomaterials affects the failure mechanism and reliability of geotechnical structures significantly, and can be modeled rigorously as a three-dimensional (3-D) random field. However, the simulation of multivariate, large-scale and high-resolution… read more here.
Keywords: random fields; cmd; large scale; three dimensional ... See more keywords
Transformations of spatial correlation lengths in random fields
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DOI: 10.1016/j.compgeo.2021.104151
Abstract: Abstract The paper describes the theoretical relationship between spatial correlation lengths in lognormal and hyperbolic tangent (“tanh”) random fields, and the underlying Gaussian random fields from which they are derived following transformation. The inevitable change… read more here.
Keywords: transformations spatial; random fields; lengths random; correlation lengths ... See more keywords