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Industrial time series modelling by means of the neo-fuzzy neuron

Zurita, D.; Delgado Prieto, M.; Cariño , J.A.; Ortega, J.A.; Clerc, G.
Tipus d'activitat
Article en revista
IEEE access
Data de publicació
DOI Obrir en finestra nova
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Abstract—Industrial process monitoring and modelling represents a critical step in order to achieve the paradigm of Zero Defect Manufacturing. The aim of this paper is to introduce the Neo-Fuzzy Neuron method to be applied in industrial time series modelling. Its open structure and input independency provides fast learning and convergence capabilities, while assuring a proper accuracy and generalization in the modelled output. First, the auxiliary signals in the database are analyzed in order ...
Zurita, D., Delgado Prieto, M., Cariño , J.A., Ortega, J.A., Clerc, G. Industrial time series modelling by means of the neo-fuzzy neuron. "IEEE access", 20 Setembre 2016.
Paraules clau
Artificial Intelligence, Forecasting, Fuzzy Neural Networks, Industrial Plants, Predictive Models, Time Series Analysis.
Grup de recerca
MCIA - Centre MCIA Innovation Electronics
PERC-UPC - Centre de Recerca d'Electrònica de Potència UPC