hh.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
A SOM-based data mining strategy for adaptive modelling of an offset lithographic printing process
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID-id: 0000-0002-1043-8773
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab).ORCID-id: 0000-0003-2185-8973
2007 (engelsk)Inngår i: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 20, nr 3, s. 391-400Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This paper is concerned with a SOM-based data mining strategy for adaptive modelling of a slowly varying process. The aim is to follow the process in a way that makes a representative up-to-date data set of a reasonable size available at any time. The technique developed allows analysis and filtering of redundant data, detection of the need to update the process models and the core-module of the system itself and creation of process models of adaptive, data-dependent complexity. Experimental investigations performed using data from a slowly varying offset lithographic printing process have shown that the tools developed can follow the process and make the necessary adaptations of the data set and the process models. A low-process modelling error has been obtained by employing data-dependent committees for modelling the process.

sted, utgiver, år, opplag, sider
Oxford: Pergamon Press, 2007. Vol. 20, nr 3, s. 391-400
Emneord [en]
Adaptive modelling, Data mining, Self-organizing map, Committee, Neural networks
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-1083DOI: 10.1016/j.engappai.2006.07.004ISI: 000245477700008Scopus ID: 2-s2.0-33847680074Lokal ID: 2082/1459OAI: oai:DiVA.org:hh-1083DiVA, id: diva2:238301
Tilgjengelig fra: 2008-01-22 Laget: 2008-01-22 Sist oppdatert: 2018-01-13bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Personposter BETA

Englund, CristoferVerikas, Antanas

Søk i DiVA

Av forfatter/redaktør
Englund, CristoferVerikas, Antanas
Av organisasjonen
I samme tidsskrift
Engineering applications of artificial intelligence

Søk utenfor DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric

doi
urn-nbn
Totalt: 348 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf