Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Abstract: In this article, we extend the popular supervised learning technique radial basis function network (RBFN) for regression modeling based on fuzzy responses ...

Abstract: In this paper, we present an extended Hermite radial basis functions interpolant for surface reconstruction of sparse contours that allows for shape control with interactive constraints.

STK is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at ...

In recent years neural computing has emerged as a practical technology, with successful applications in many fields. The majority of these applications are concerned with problems in pattern ...

FLOWVPM implements the reformulated vortex particle method (rVPM) developed in E. J. Alvarez' doctoral dissertation Reformulated Vortex Particle Method and Meshless Large Eddy Simulation of Multirotor ...

Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation ...

Radial Basis Function methods for scattered data interpolation and for the numerical solution of PDEs were originally implemented in a global manner. Subsequently, it was realized that the methods ...