On similarities between two models of global optimization: statistical models and radial basis functions

摘要

Construction of global optimization algorithms using statistical models and radial basis function models is discussed. A new method of data smoothing using radial basis function and least squares approach is presented. It is shown that the P-algorithm for global optimization in the presence of noise based on a statistical model coincides with the corresponding radial basis algorithm.