A traditional criterion to calculate the numerical stability of the interpolation matrix is its
standard condition number. In this paper, it is observed that the effective condition number (κ …

Continuously monitoring surface ozone (O 3) spatial distribution and forecasting its
variations are beneficial to improving air quality and ensuring public health in China …

Surface O 3 pollution severely threats human health and crop production across the globe.
Data-driven machine learning approaches are broadly used for estimating surface O 3 …

In this work we develop the standard Hermite interpolation based RBF-generated finite
difference (RBF-HFD) method into a new faster and more accurate technique based on …

In kernel-based approximation, the tuning of the so-called shape parameter is a
fundamental step for achieving an accurate reconstruction. Recently, the popular Rippa's …

Thanks to their easy implementation via radial basis functions (RBFs), meshfree kernel
methods have proved to be an effective tool for, eg, scattered data interpolation, PDE …

This paper explores the utilization of randomized SVD (rSVD) in the context of kernel
matrices arising from radial basis functions (RBFs) for the purpose of solving interpolation …

This study presents a novel ensemble of surface ozone (O3) generated by the LEarning
Surface Ozone (LESO) framework. The aim of this study is to investigate the spatial and …

To enable an evidence-based management of ecosystems to adapt to the climate crisis, we
require fine spatiotemporal resolution estimates of carbon, water, and energy fluxes at the …

In this paper we present a new fast and accurate method for Radial Basis Function (RBF)
approximation, including interpolation as a special case, which enables us to effectively find …