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Rule induction for structural damage identification
KTH, Superseded Departments (pre-2005), Numerical Analysis and Computer Science, NADA.
2004 (English)In: Proc. Int. Conf. Mach. Learning Cybernetics, 2004, p. 2865-2869Conference paper, Published paper (Refereed)
Abstract [en]

Structural damage identification is becoming a worldwide research subject. Some machine learning methods have been used to solve this problem, and most of them are neural network methods. In this paper, three different rule inductive methods named as Divide-and-Conquer (DAC), Bagging and Separate-and-Conquer (SAC) are investigated for predicting the damage position and extent of a concrete beam. Then radial basis function neural network (RBFNN) is used here for comparative purposes. The rule inductive methods/ especially Bagging are shown to obtain good prediction.

Place, publisher, year, edition, pages
2004. p. 2865-2869
Series
Proceedings of 2004 International Conference on Machine Learning and Cybernetics ; 5
Keyword [en]
Bagging, Divide-and-Conquer, Rule induction, Separate-and-Conquer, Structural damage identification, Backpropagation, Data acquisition, Elastic moduli, Information retrieval, Learning systems, Mathematical models, Multilayer neural networks, Radial basis function networks, Identification (control systems)
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-156946ISI: 000225293600564Scopus ID: 2-s2.0-6344229873ISBN: 0780384032 (print)OAI: oai:DiVA.org:kth-156946DiVA, id: diva2:768905
Conference
Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 26-29 August 2004, Shanghai, China
Note

QC 20141205

Available from: 2014-12-05 Created: 2014-12-04 Last updated: 2018-01-16Bibliographically approved

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Boström, Henrik

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Citation style
  • apa
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  • ieee
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More styles
Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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