Analysis of a hybrid neural network as underlying mechanism for a situation prediction engine

Authors

  • Carlos Oberdan Rolim Institute of Informatics — Federal University of Rio Grande do Sul — UFRGS Av. Bento Gonçalves 9500, Block IV, Building 72, Agronomia. Post Office Box: 15064 — Porto Alegre/RS, Brazil Phone: +55 (51) 3308 6161
  • Anubis G.M. Rossetto Universidade Federal do Rio Grande do Sul.
  • Valderi R.Q. Leithardt Universidade Federal do Rio Grande do Sul.
  • Claudio F.R. Geyer Universidade Federal do Rio Grande do Sul.

DOI:

https://doi.org/10.4013/jacr.2012.21.03

Abstract

This paper presents the results regarding a technique that can be used as an underlying mechanism for situation prediction. We analysed a hybrid neural network called Multi-output Adaptive Neural Fuzzy Inference System (MANFIS) and compared its predictive ability with a Multi-Layer Perceptron (MLP). The results demonstrate that, depending on the application, the use of neural networks can be considered to be a good approach for situation prediction, when combined with other techniques.

Key words: situation, context, prediction, neural networks, MANFIS.

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Published

2012-12-21

Issue

Vol. 2 No. 1 (2012): Jan-Jun

Section

Articles

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