Difference between revisions of "Publications:Combining traditional and neural-based techniques for ink feed control in a newspaper printing press"

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|Name=Englund, Cristofer [cren] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], Intelligenta system (IS-lab) [3941]);Verikas, Antanas [av] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], Intelligenta system (IS-lab) [3941])
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|Name=Englund, Cristofer [crieng] [0000-0002-1043-8773] (Högskolan i Halmstad [2804], Akademin för informationsteknologi [16904], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], Intelligenta system (IS-lab) [3941]);Verikas, Antanas [av] [0000-0003-2185-8973] (Högskolan i Halmstad [2804], Akademin för informationsteknologi [16904], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], Intelligenta system (IS-lab) [3941])
 
|Title=Combining traditional and neural-based techniques for ink feed control in a newspaper printing press
 
|Title=Combining traditional and neural-based techniques for ink feed control in a newspaper printing press
 
|PublicationType=Conference Paper
 
|PublicationType=Conference Paper
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|CreatedDate=2007-12-28
 
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|PublicationDate=2007-12-28
|LastUpdated=2012-10-04
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|LastUpdated=2016-02-24
 
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Revision as of 20:47, 30 September 2016

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Title Combining traditional and neural-based techniques for ink feed control in a newspaper printing press
Author
Year 2007
PublicationType Conference Paper
Journal
HostPublication Advances in Data Mining : Theoretical Aspects and Applications, Proceedings
Conference 7th Industrial Conference on Data Mining, Leipzig, GERMANY, JUL 14-18, 2007
DOI http://dx.doi.org/10.1007/11427391_73
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:238286
Abstract

A SOM based model combination strategy, allowing to create adaptive – data dependent – committees, is proposed. Both, models included into a committee and aggregation weights are specific for each input data point analyzed. The possibility to detect outliers is one more characteristic feature of the strategy.