d_eff in PINNs is shown to be an operator invariant equal to kernel dimension for finite-kernel operators, enabling subspace projection for physics-preserving constraint adaptation.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A domain-mapped functional link neural network solves static bending of perforated nanobeams and is compared to Galerkin results for dynamic deflection.
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Comparative Study of Bending Analysis using Physics-Informed Neural Networks and Numerical Dynamic Deflection in Perforated nanobeam
A domain-mapped functional link neural network solves static bending of perforated nanobeams and is compared to Galerkin results for dynamic deflection.