A non-linear optimization model and ANFIS-based approach to knowledge acquisition to classify service systems

Abstract

This paper studies the problem of knowledge acquisition to classify service systems. We define a set of attributes and characteristics in order to classify the service systems. To state the interactions between attributes and characteristics we propose a non-linear optimization model and an adaptive neuro-fuzzy inference system (ANFIS) approach. We compare both approaches in terms of mean root square error in a data test based in International Standard Industrial Classification. Our results present a better performance of ANFIS approach over a set of data collected about ISIC classification in Colombia industries.