Unified estimate of Gaussian kernel width for surrogate models

This paper presents a novel approach for estimating the Gaussian kernel width widely employed in radial basis function (RBF) network, support vector machine (SVM), Kriging models, etc. As widely known, the Gaussian kernel width in these surrogate models is highly significant, and estimating the appropriate applicable width is usually an arduous task. Therefore, the need to develop a simple method to determine the kernel width becomes imperative....