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2016 | OriginalPaper | Buchkapitel

A Non-linear Optimization Model and ANFIS-Based Approach to Knowledge Acquisition to Classify Service Systems

verfasst von : Eduyn Ramiro López-Santana, Germán Andrés Méndez-Giraldo

Erschienen in: Intelligent Computing Methodologies

Verlag: Springer International Publishing

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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.

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Metadaten
Titel
A Non-linear Optimization Model and ANFIS-Based Approach to Knowledge Acquisition to Classify Service Systems
verfasst von
Eduyn Ramiro López-Santana
Germán Andrés Méndez-Giraldo
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-42297-8_73