ABSTRACT: This paper presents the mathematical models and calculation of states of matter dynamics (gasses, fluids, solids) and phase transitions from statistical viewpoint, with new calculation ...

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...

Functions are the building blocks of Python programming. They let you organize your code, reduce repetition, and make your programs more readable and reusable. Whether you’re writing small scripts or ...

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 ...

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Abstract: Radial basis function neural networks (RBFNN) which are best suited for nonlinear function approximation, have been successfully applied to a wide range of areas including system modeling.

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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 ...