Model of Least Square Support Vector Machine (LSSVM) for Prediction of Fracture Parameters of Concrete

ABOUT THE INTERNATIONAL CONCRETE ABSTRACTS PORTAL

  • The International Concrete Abstracts Portal is an ACI led collaboration with leading technical organizations from within the international concrete industry and offers the most comprehensive collection of published concrete abstracts.

International Concrete Abstracts Portal

  


Title: Model of Least Square Support Vector Machine (LSSVM) for Prediction of Fracture Parameters of Concrete

Author(s): Kulkrni Kallyan S., Dookie Kim, S. K. Sekar, and Pijush Samui

Publication: IJCSM

Volume: 5

Issue: 1

Appears on pages(s): 29-33

Keywords: least square support vector machine (LSSVM); fracture mechanics; artificial neural network (ANN); support vector machine (SVM)

Date: 6/30/2011

Abstract:
This article employs Least Square Support Vector Machine (LSSVM) for determination of fracture parameters of concrete: critical stress intensity factor ( ) and the critical crack tip opening displacement ( ). 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 and , and then a sensitivity analysis has been performed to investigate the importance of the input parameters. Equations have been also developed for determination of and . 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.


IJCSM, International Partner Access.

View Resource »