Results 51 to 60 of about 12,800 (234)
On the Performance of Neural Network Residual Kriging in Radio Environment Mapping
IEEE Access, 2019 This paper addresses the research question: can feedforward neural network (FFNN)-based path loss modeling improve the accuracy of Kriging? Radio propagation factors, which consist of path loss and shadowing, can accurately be obtained via crowdsourcing ...
Koya Sato, Kei Inage, Takeo Fujii
doaj +1 more source
Polymer Composites, EarlyView.Overview of the holistic engineering lifecycle and core research pillars for wind turbine blades. ABSTRACT This paper reviews recent advancements across the lifecycle of wind turbine blades, focusing on three interconnected areas: advanced composites, structural optimization, and machine learning (ML) diagnostics. In materials, we highlight progress in
Kemal Hasirci +2 more
wiley +1 more source
Polymer Composites, EarlyView.An integrated experimental, numerical, and explainable machine learning framework for the material‐geometric co‐optimization and multi‐objective Pareto design of robust composite adhesive joints. ABSTRACT The reliability of composite adhesive joints is compromised by non‐linear dependencies between material properties and manufacturing uncertainties ...
Sajjad Karimi
wiley +1 more source
Epistemic and aleatoric uncertainty quantification in weather and climate models
Quarterly Journal of the Royal Meteorological Society, EarlyView.Aleatoric and epistemic uncertainties over time on weather and climate time‐scales, estimated through ensembles that sample aleatoric and epistemic uncertainty using Bayesian neural networks for parameterisations in the Lorenz 1996 model. The spread shows the 16th and 84th percentiles.
Laura A. Mansfield +1 more
wiley +1 more source
Spatial Estimation of Sodium Adsorption Ratio (SAR) and Chlorine in Groundwater Using Geostatistical Methods [PDF]
علوم و مهندسی آبیاری, 2011 Having knowledge of groundwater quality in arid and semi-arid areas can result sustainability of this valuable resource. For this reason, it is necessary to estimate Sodium Adsorption Ratio (SAR) and Chlorine in the groundwater quality accurately ...
A. Izadi +3 more
doaj
Technometrics, 2017 We consider the problem of constructing metamodels for computationally expensive simulation codes; that is, we construct interpolation/prediction of functions values (responses) from a finite collection of evaluations (observations). We use Gaussian process modeling and Kriging, and combine a Bayesian approach, based on a finite set of covariance ...
Pronzato, Luc, Rendas, Joaõ
openaire +2 more sources
Quarterly Journal of the Royal Meteorological Society, EarlyView.The introduction of adaptive parameter tuning in the numerical weather prediction models of DWD in 2022 substantially improved the forecast quality of near‐surface variables like 2‐m temperature and 2‐m humidity. Since 2023, refinements and extensions, primarily affecting the surface evaporation and its diurnal cycle, have led to further advances ...
Günther Zängl
wiley +1 more source
Facies-Constrained Kriging Interpolation Method for Parameter Modeling
Remote SensingIn seismic exploration, establishing a reliable parameter model (such as velocity, density, impedance) is crucial for seismic migration imaging and reservoir characterization.
Zhenbo Nie +5 more
doaj +1 more source
Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño +6 more
wiley +1 more source
Reliability analysis of high-lift device wear based on indicator error control Kriging
Xibei Gongye Daxue XuebaoTo address the issues that the Kriging surrogate model using the learning function as the convergence criterion cannot reflect the accuracy of predicted failure probability directly and accurately and incur high computational cost in modeling, a ...
FENG Yunwen +6 more
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