Design of ANFIS networks using hybrid genetic and SVD methods for the modelling of explosive cutting process

Abstract

Genetic algorithm (GA) and singular value decomposition (SVD) are deployed simultaneously for optimal design of both Gaussian membership functions of antecedents and vector of linear coefficients of consequents, respectively, of ANFIS networks which are used for modelling of explosive cutting process of plates by shaped charges. The aim of such modelling is to show how the depth of penetration varies with the variation of important parameters namely, apex angle, standoff, liner thickness, and mass of charge. It is demonstrated that SVD can be effectively used to optimally find the vector of linear coefficients of conclusion parts in ANFIS models whilst their Gaussian membership functions in premise parts are determined by GA.