Please use this identifier to cite or link to this item:
https://hdl.handle.net/11499/4687
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | İplikçi, Serdar | - |
dc.date.accessioned | 2019-08-16T11:36:18Z | |
dc.date.available | 2019-08-16T11:36:18Z | |
dc.date.issued | 2006 | - |
dc.identifier.isbn | 03029743 (ISSN) | - |
dc.identifier.isbn | 3540386254 | - |
dc.identifier.isbn | 9783540386254 | - |
dc.identifier.uri | https://hdl.handle.net/11499/4687 | - |
dc.description.abstract | In this study, the previously proposed Online Support Vector Machines Based Generalized Predictive Control method [1] is applied to the problem of stabilizing discrete-time chaotic systems with small parameter perturbations. The method combines the Accurate Online Support Vector Regression (AOSVR) algorithm [2] with the Support Vector Machines Based Generalized Predictive Control (SVM-Based GPC) approach [3] and thus provides a powerful scheme for controlling chaotic maps in an adaptive manner. The simulation results on chaotic maps have revealed that Online SVM-Based GPC provides an excellent online stabilization performance and maintains it when some measurement noise is added to output of the underlying map. © Springer-Verlag Berlin Heidelberg 2006. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer Verlag | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Computer simulation | en_US |
dc.subject | Online systems | en_US |
dc.subject | Perturbation techniques | en_US |
dc.subject | Predictive control systems | en_US |
dc.subject | Regression analysis | en_US |
dc.subject | Vectors | en_US |
dc.subject | Accurate Online Support Vector Regression (AOSVR) algorithm | en_US |
dc.subject | Online stabilization | en_US |
dc.subject | Support Vector Machines Based Generalized Predictive Control (SVM-Based GPC) approach | en_US |
dc.subject | Chaos theory | en_US |
dc.title | Online stabilization of chaotic maps via support vector machines based generalized predictive control | en_US |
dc.type | Conference Object | en_US |
dc.identifier.volume | 4131 LNCS - I | en_US |
dc.identifier.startpage | 868 | |
dc.identifier.startpage | 868 | en_US |
dc.identifier.endpage | 877 | en_US |
dc.authorid | 0000-0003-3806-1442 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopus | 2-s2.0-33749835807 | en_US |
dc.identifier.wos | WOS:000241472100090 | en_US |
dc.owner | Pamukkale_University | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.openairetype | Conference Object | - |
item.grantfulltext | none | - |
crisitem.author.dept | 10.10. Computer Engineering | - |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
CORE Recommender
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.