Abstract: This paper proposes a novel neural network architecture RBF-KAN, integrating the theoretical robustness of Kolmogorov-Arnold Networks (KANs) with the localized features of Radial Basis ...
This study presents a novel local meshless approach for solving one-dimensional Fisher’s equation, combining a local scheme, Gaussian radial basis functions (G-RBF), and a collocation technique. The ...
RNA interference using small interfering RNAs (siRNAs) has become a mainstay of functional gene characterization and has generated over a dozen FDA-approved therapeutics and drugs in late-stage ...
In this work, we introduce a new method ability radial basic function-partial least square (RBF-PLS) with high accuracy and precision in QSPR studies. Three quantitative structure-propertty ...
ABSTRACT: We solve numerically an eigenvalue elliptic partial differential equation (PDE) ranging from two to six dimensions using the generalized multiquadric (GMQ) radial basis functions (RBFs). Two ...
Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...
Intelligent vehicles and autonomous driving have been the focus of research in the field of transport, but current autonomous driving models have significant errors in lateral tracking that cannot be ...
Radial Basis Function Neural Networks (RBFNNs) are a type of neural network that combines elements of clustering and function approximation, making them powerful for both regression and classification ...
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