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  • Van Blokland, Joran, et al. (author)
  • Machine learning-based prediction of surface checks and bending properties in weathered thermally modified timber
  • 2021
  • In: Construction and Building Materials. - : Elsevier BV. - 0950-0618. ; 307
  • Journal article (peer-reviewed)abstract
    • Machine learning (ML)-based models, decision tree and ANFIS, were used to predict the degree of surface checking and bending properties of 30-month weathered thermally modified timber. The results showed that the investigated initial board properties did not allow accurate predictions of surface checks. ML regression and clustering analysis confirmed important variables for accurate predictions of bending properties were dynamic stiffness, acoustic velocity, density and lowest local bending modulus. ML models performed better than conventional regression models used for timber grading, and a prediction accuracy of 80–90% for bending stiffness and 50–70% for bending strength could be achieved.
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Type of publication
journal article (1)
Type of content
peer-reviewed (1)
Author/Editor
Adamopoulos, Stergio ... (1)
Van Blokland, Joran (1)
University
Swedish University of Agricultural Sciences (1)
Language
English (1)
Research subject (UKÄ/SCB)
Agricultural Sciences (1)
Year
2021 (1)

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