Analysis of a hybrid neural network as underlying mechanism for a situation prediction engine
Author(s) -
Carlos Oberdan Rolim,
Anubis G.M. Rossetto,
Valderi Reis Quietinho Leithardt,
Cláudio F. R. Geyer
Publication year - 2012
Publication title -
journal of applied computing research
Language(s) - English
Resource type - Journals
ISSN - 2236-8434
DOI - 10.4013/jacr.2012.21.03
Subject(s) - artificial neural network , computer science , artificial intelligence , adaptive neuro fuzzy inference system , perceptron , mechanism (biology) , context (archaeology) , machine learning , neuro fuzzy , key (lock) , multilayer perceptron , inference system , fuzzy logic , fuzzy control system , paleontology , philosophy , computer security , epistemology , biology
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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