Ensemble RBF modeling technique for quality design

Abstract

This paper proposes an ensemble radial basis function neural network that selects important RBF subsets based on Pareto chart using Bootstrap samples. Then, the analysis of variance method is used to determine the choice of the unequal/equal weights. The effectiveness of the proposed technique is illustrated with a micro-drilling process. The comparison results show that the proposed technique can not only improve the model prediction performance, but also generate a reliable scheme for quality design. Keywords: RBF model, Ensemble model, Model selection, Pareto chart, Process optimization