Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • 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
Using Uncertain Chemical and Thermal Data to Predict Product Quality in a Casting Process
University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.ORCID iD: 0000-0001-8382-0300
2009 (English)In: U '09: Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data / [ed] Jian Pei, Lise Getoor, Ander De Keijzer, ACM Digital Library, 2009, p. 57-61Conference paper, Published paper (Refereed)
Abstract [en]

Process and casting data from different sources have been collected and merged for the purpose of predicting, and determining what factors affect, the quality of cast products in a foundry. One problem is that the measurements cannot be directly aligned, since they are collected at different points in time, and instead they have to be approximated for specific time points, hence introducing uncertainty. An approach for addressing this problem is investigated, where uncertain numeric features values are represented by intervals and random forests are extended to handle such intervals. A preliminary experiment shows that the suggested way of forming the intervals, together with the extension of random forests, results in higher predictive performance compared to using single (expected) values for the uncertain features together with standard random forests.

Place, publisher, year, edition, pages
ACM Digital Library, 2009. p. 57-61
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3418DOI: 10.1145/1610555.1610563Scopus ID: 2-s2.0-70450267831ISBN: 978-1-60558-675-5 (print)OAI: oai:DiVA.org:his-3418DiVA, id: diva2:272096
Conference
1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data, U'09 in conjunction with KDD'09, The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, 28 June 2009 through 28 June 2009, Code 77977
Available from: 2009-10-14 Created: 2009-10-14 Last updated: 2020-08-04Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Dudas, CatarinaBoström, Henrik

Search in DiVA

By author/editor
Dudas, CatarinaBoström, Henrik
By organisation
School of Technology and SocietyThe Virtual Systems Research CentreSchool of Humanities and InformaticsThe Informatics Research Centre
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 724 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • 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