Extracting sensitivity information of electromagnetic device models using a modified ANFIS topology

This paper addresses the problem of extracting sensitivity information from a modified adaptive-network-based fuzzy inference system (ANFIS) topology, i.e., from a Parallel Layer Perceptron network. This topology was recently proposed and presents computational advantages if compared with the traditional ANFIS. The indirect extraction of gradient information is useful in optimization problems when a high computational effort is involved in the evaluation of the functions, for instance when finite element analysis is used to solve the electromagnetic field problem. An analytical and an electromagnetic optimization problem are discussed. The results show the effectiveness, i.e., simplicity, accuracy and saving in CPU time, of this novel topology for the extraction of sensitivity information.