Adaptive LOOCV-based kernel methods for solving time-dependent BVPs

Roberto Cavoretto

Applied Mathematics and Computation, 2022, vol. 429, issue C

Abstract: In this article we propose an adaptive algorithm for the solution of time-dependent boundary value problems (BVPs). To solve numerically these problems, we consider the kernel-based method of lines that allows us to split the spatial and time derivatives, dealing with each separately. This adaptive scheme is based on a leave-one-out cross validation (LOOCV) procedure, which is employed as an error indicator. By this technique, we can first detect the domain areas where the error is estimated to be too large – generally due to steep variations or quick changes in the solution – and then accordingly enhance the numerical solution by applying a two-point refinement strategy. Numerical experiments show the efficacy and performance of our adaptive refinement method.

Keywords: Meshless approximation; Kernel methods; Adaptive algorithms; Refinement schemes; Partial differential equations (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:429:y:2022:i:c:s0096300322003022

DOI: 10.1016/j.amc.2022.127228

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