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A hybrid approach to outlier detection in the offset lithographic printing process
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).ORCID iD: 0000-0002-1043-8773
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).ORCID iD: 0000-0003-2185-8973
2005 (English)In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 18, no 6, p. 759-768Article in journal (Refereed) Published
Abstract [en]

Artificial neural networks are used to model the offset printing process aiming to develop tools for on-line ink feed control. Inherent in the modelling data are outliers owing to sensor faults, measurement errors and impurity of materials used. It is fundamental to identify outliers in process data in order to avoid using these data points for updating the model. We present a hybrid, the process-model-network-based technique for outlier detection. The outliers can then be removed to improve the process model. Several diagnostic measures are aggregated via a neural network to categorize data points into the outlier and inlier classes. We demonstrate experimentally that a soft fuzzy expert can be configured to label data for training the categorization of neural network.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2005. Vol. 18, no 6, p. 759-768
Keywords [en]
Neural network, Outlier detection, Leverages, Fuzzy expert
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:hh:diva-260DOI: 10.1016/j.engappai.2005.01.008ISI: 000230338700010Scopus ID: 2-s2.0-20144370706Local ID: 2082/555OAI: oai:DiVA.org:hh-260DiVA, id: diva2:237439
Available from: 2006-11-24 Created: 2006-11-24 Last updated: 2025-02-07Bibliographically approved

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Englund, CristoferVerikas, Antanas

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf