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Multimodal forecasting methodology applied to industrial process monitoring

Autor
Zurita, D.; Delgado Prieto, M.; Cariño , J.A.; Ortega, J.A.
Tipus d'activitat
Article en revista
Revista
IEEE transactions on industrial informatics
Data de publicació
2017-09-20
Pàgina inicial
1
Pàgina final
10
DOI
https://doi.org/10.1109/TII.2017.2755099 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/109279 Obrir en finestra nova
URL
http://ieeexplore.ieee.org/document/8048029/ Obrir en finestra nova
Resum
IEEE Industrial process modelling represents a key factor to allow the future generation of industrial manufacturing plants. In this regard, accurate models of critical signals need to be designed in order to forecast process deviations. In this work a novel multimodal forecasting methodology based on adaptive dynamics packaging and codification of the process operation is proposed. First, a target signal is decomposed by means of the Empirical Mode Decomposition in order to identify the charact...
Citació
Zurita, D., Delgado Prieto, M., Cariño , J.A., Ortega, J.A. Multimodal forecasting methodology applied to industrial process monitoring. "IEEE transactions on industrial informatics", 20 Setembre 2017, p. 1-10.
Paraules clau
Adaptation models, Biological system modeling, Computational modeling, Forecasting, Fuzzy neural networks, Industrial plants, Packaging, Predictive models, Time series analysis
Grup de recerca
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Centre de Recerca d'Electrònica de Potència UPC

Participants

Arxius