AQUARS algorithms that use a radial basis function model and compare them with alternative global optimization methods on an …

experiments, and Taguchi Orthogonal Array (OA). Then, metamodel is constructed by Radial Basis Function Neural Network (RBFNN) to …

context of linear inverse problems. Radial basis function regularization is widely used in machine learning because of its … advantages of radial basis function regularization in general and Gaussian radial basis function regularization in particular is … radial basis function regularization. …

Purpose – The purpose of this paper is to present the radial basis function (RBF) networks‐based adaptive robust …

A novel neural architecture for prediction in industrial control: the 'Double Recurrent Radial Basis Function network … method, a simple architecture is proposed consisting of two simple Recurrent Radial Basis Function networks (RRBF). Each RRBF … the Radial Basis Function (RBF) nodes. The K-means unsupervised learning algorithm used for the hidden layer is enhanced …

to keep in account the change of all the parameters at different operating conditions. Radial basis function neural …