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Visualization of dynamics using local dynamic modelling with self organizing maps

dc.contributor.authorDíaz Blanco, Ignacio 
dc.contributor.authorCuadrado Vega, Abel Alberto 
dc.contributor.authorDíez González, Alberto Benjamín 
dc.contributor.authorFuertes Martínez, Juan José
dc.contributor.authorDomínguez González, Manuel
dc.contributor.authorReguera Acevedo, Perfecto
dc.date.accessioned2014-02-24T10:41:51Z
dc.date.available2014-02-24T10:41:51Z
dc.date.issued2007
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10651/22842
dc.description.abstractIn this work, we describe a procedure to visualize nonlinear process dynamics using a self-organizing map based local model dynamical estimator. The proposed method exploits the topology preserving nature of the resulting estimator to extract visualizations (planes) of insightful dynamical features, that allow to explore nonlinear systems whose behavior changes with the operating point. Since the visualizations are obtained from a dynamical model of the process, measures on the goodness of this estimator (such as RMSE or AIC) are also applicable as a measure of the trustfulness of the visualizations. To illustrate the application of the proposed method, an experiment to analyze the dynamics of a nonlinear system on different operating points is included
dc.format.extentp. 609-617
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rights© Springer
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleVisualization of dynamics using local dynamic modelling with self organizing maps
dc.typeconference outputspa
dc.identifier.doi10.1007/978-3-540-74690-4_62
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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