International Journal of Concrete Structures and Materials

  • 제5권1호
  • /
  • Pages.29-33
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  • 2011
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  • 1976-0485(pISSN)
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  • 2234-1315(eISSN)
한국콘크리트학회 (Korea Concrete Institute)
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Model of Least Square Support Vector Machine (LSSVM) for Prediction of Fracture Parameters of Concrete

  • Kulkrni, Kallyan S. (Structural Engineering, VIT University) ;
  • Kim, Doo-Kie (Department of Civil Engineering, Kunsan National University) ;
  • Sekar, S.K. (Centre for Disaster Mitigation and Management, VIT University) ;
  • Samui, Pijush (Centre for Disaster Mitigation and Management, VIT University)
  • 투고 : 2010.11.01
  • 심사 : 2011.03.03
  • 발행 : 2011.06.30
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초록

This article employs Least Square Support Vector Machine (LSSVM) for determination of fracture parameters of concrete: critical stress intensity factor ($K_{Ic}^s$) and the critical crack tip opening displacement ($CTOD_c$). LSSVM that is firmly based on the theory of statistical learning theory uses regression technique. The results are compared with a widely used Artificial Neural Network (ANN) Models of LSSVM have been developed for prediction of $K_{Ic}^s$ and $CTOD_c$, and then a sensitivity analysis has been performed to investigate the importance of the input parameters. Equations have been also developed for determination of $K_{Ic}^s$ and $CTOD_c$. The developed LSSVM also gives error bar. The results show that the developed model of LSSVM is very predictable in order to determine fracture parameters of concrete.

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참고문헌

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