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

Carlos Oberdan Rolim, Anubis G.M. Rossetto, Valderi R.Q. Leithardt, Claudio F.R. Geyer


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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This work is licensed under a Creative Commons Attribution 4.0 International License. [updated on August 2016]

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