A Radial Basis Function network training algorithm using a non-symmetric partition of the input space

dc.contributor.author	Αλεξανδρίδης, Αλέξανδρος Π.	el
dc.contributor.author	Σαρίμβεης, Χαράλαμπος Κ.	el
dc.contributor.author	Νίνος, Κωνσταντίνος Δ.	el
dc.date.accessioned	2015-05-14T18:34:01Z
dc.date.available	2015-05-14T18:34:01Z
dc.date.issued	2015-05-14
dc.identifier.uri	http://hdl.handle.net/11400/10417
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.sciencedirect.com	en
dc.subject	Neural networks (Computer science)
dc.subject	Radial basis functions
dc.subject	Predictive control
dc.subject	νευρωνικά δίκτυα
dc.subject	ακτινική συνάρτηση βάσης
dc.subject	ασαφή μέσα
dc.subject	ασαφής κατανομή
dc.subject	μη συμμετρική κατανομή
dc.subject	μοντέλο πρόβλεψης ελέγχου
dc.subject	συνεχής ανάδευση δεξαμενής αντιδραστήρα
dc.subject	Fuzzy means
dc.subject	Fuzzy partition
dc.subject	Non-symmetric partition
dc.subject	Mackey-Glass
dc.subject	continuous stirred tank reactor
dc.title	A Radial Basis Function network training algorithm using a non-symmetric partition of the input space	en
heal.type	journalArticle
heal.secondaryTitle	application to a model predictive control configuration	en
heal.classification	Τεχνολογία
heal.classification	Ηλεκτρονική
heal.classification	Technology
heal.classification	Electrical engineering
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Ηλεκτρονική
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://skos.um.es/unescothes/C01311
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh90001937
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2002004691
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh92000169
heal.identifier.secondary	DOI: 10.1016/j.advengsoft.2011.05.026
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Ηλεκτρονικών Μηχανικών Τ.Ε.	el
heal.publicationDate	2011-10
heal.bibliographicCitation	Alexandridis, A.P., Sarimveis, H.K. & Ninos, K. (2011). A Radial Basis Function network training algorithm using a non-symmetric partition of the input space: application to a Model Predictive Control configuration. "Advances in Engineering Software". 42(10): p. 830-3-837	en
heal.abstract	This work presents the non-symmetric fuzzy means algorithm which is a new methodology for training Radial Basis Function neural network models. The method is based on a non-symmetric fuzzy partition of the space of input variables which results to networks with smaller structures and better approximation capabilities compared to other state-of-the-art training procedures. The lower modeling error and the smaller size of the produced models become particularly important when they are used in online applications. This is demonstrated by integrating the model produced by the proposed algorithm in a Model Predictive Control configuration, resulting in better control performance and shorter computational times.	en
heal.journalName	Advances in Engineering Software	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true