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Authors: Messaoud Bouakkaz and Mohamed-Faouzi Harkat

Affiliation: University Badji Mokhtar-Annaba, Algeria

ISBN: 978-989-8565-33-4

Keyword(s): Nonlinear PCA, IT-net, RBF-neural Network, Process Monitoring, Fault Detection and Isolation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Based Data Mining and Complex Information Processing ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: In this paper a novel Nonlinear Principal Component Analysis (NLPCA) is proposed. Generally, a NLPCA model is performed by using two sub-models, mapping and demapping. The proposed NLPCA model consists of two cascade three-layer neural networks for mapping and demapping, respectively. The mapping model is identified by using a Radial Basis Function (RBF) neural networks and the demapping is performed by using an Input Training neural networks (IT-Net). The nonlinear principal components, which represents the desired output of the first network, are obtained by the IT-NET. The proposed approach is illustrated by a simulation example and then applied for fault detection and isolation of the TECP process.

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Paper citation in several formats:
Bouakkaz, M. and Harkat, M. (2012). Combined Input Training and Radial Basis Function Neural Networks based Nonlinear Principal Components Analysis Model Applied for Process Monitoring.In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 483-492. DOI: 10.5220/0004152304830492

@conference{ncta12,
author={Messaoud Bouakkaz. and Mohamed{-}Faouzi Harkat.},
title={Combined Input Training and Radial Basis Function Neural Networks based Nonlinear Principal Components Analysis Model Applied for Process Monitoring},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)},
year={2012},
pages={483-492},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004152304830492},
isbn={978-989-8565-33-4},
}

TY - CONF

JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)
TI - Combined Input Training and Radial Basis Function Neural Networks based Nonlinear Principal Components Analysis Model Applied for Process Monitoring
SN - 978-989-8565-33-4
AU - Bouakkaz, M.
AU - Harkat, M.
PY - 2012
SP - 483
EP - 492
DO - 10.5220/0004152304830492

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