Dalarna University's logo and link to the university's website

du.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • 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
Classification of structural timber by decision trees: a comparison to the certified method
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-0403-338X
2009 (English)In: Forest Products Journal, ISSN 0015-7473, Vol. 59, no 3, p. 53-61Article in journal (Refereed) Published
Abstract [en]

This work is an example of how to adapt a classification method, in this case a classification tree, to the present standardized method for the development of settings for strength grading machines. Data from commercially available industrial strength grading equipment were used on a large sample (approximately 1440 pieces) of Norway spruce (Picea abies (L. Karsten)) in various sawn dimensions. The equipment is a multisensor scanning device combining planar X-ray and resonance frequency measurement. Destructive testing was done according to European standard EN408. The goal was to make the classification, based on machine data, as close as possible to the optimum grading, which was done according to standard. Two different approaches for classification by cost-sensitive decision trees were applied to the data and compared to classification accredited according to EN14081. Classification accuracy increased from 64% correctly classified to 73%, and a reduction from 33% False Negative to 23% was achieved. False Positive increased from 3% to 4%. The outcome was an increase in value for the producer by 0.9%–2.1% at 2007 average price level. The improvement came mainly from an in-yield increase in C30 by 10%.

Place, publisher, year, edition, pages
Madison WI: Forest Products Society , 2009. Vol. 59, no 3, p. 53-61
Keywords [en]
C4.5, classification, data mining, density, MetaCost, Picea abies, strength grading, resonance frequency, trees, wood, X-ray
National Category
Wood Science Computer and Information Sciences
Identifiers
URN: urn:nbn:se:du-3689ISI: 000265659800007OAI: oai:dalea.du.se:3689DiVA, id: diva2:520012
Available from: 2009-02-02 Created: 2009-02-02 Last updated: 2024-07-04Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records

Westin, Jerker

Search in DiVA

By author/editor
Westin, Jerker
By organisation
Computer Engineering
In the same journal
Forest Products Journal
Wood ScienceComputer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 958 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • 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