Browse > Article
http://dx.doi.org/10.4334/IJCSM.2011.5.1.029

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)
Publication Information
International Journal of Concrete Structures and Materials / v.5, no.1, 2011 , pp. 29-33 More about this Journal
Abstract
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.
Keywords
least square support vector machine (LSSVM); fracture mechanics; artificial neural network (ANN); support vector machine (SVM);
Citations & Related Records
연도 인용수 순위
  • Reference
1 Hilsdorf, H. H. and Brameshuber, W., "Code-Type Formulation of Fracture Mechanics Concepts for Concrete," Int. J. Fract., Vol. 51, No. 1, 1991, pp. 61-72.   DOI
2 Ragip, Ince., "Prediction of Fracture Parameters of Concrete by Artificial Neural Networks," Engineering Fracture Mechanics, Vol. 71, 2004, pp. 2143-2159.   DOI   ScienceOn
3 Park, D. and Rilett, L. R., "Forecasting Freeway Link Travel Times with a Multi-Layer Feed forward Neural Network," Computer Aided Civil and infra Structure Engineering, Vol. 14, 1999, pp. 358-367.
4 Kecman, V., "Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models," MIT Press, Cambridge, Massachusetts, London, England, 2001.
5 Liong, S. Y., Lim, W. H., and Paudyal, G. N., "River Stage Forecasting in Bangladesh: Neural Network Approach," Journal of Computing in Civil Engineering, Vol. 14, No. 1, 2000, pp. 1-8.   DOI   ScienceOn
6 Suykens, J. A. K., Lukas, L., Van, D. P., De, M. B., and Vandewalle, J., "Least Squares Support Vector Machine Classifiers: a Large Scale Algorithm," In Proc. Eur. Conf. Circuit Theory and Design (ECCTD'99), Stresa, Italy, 1999, pp. 839-842.
7 Vapnik, V. and Lerner, A., "Pattern Recognition Using Generalized Portrait Method," Automation and Remote Control, Vol. 24, 1963, pp. 774-780.
8 Suykens, J. A. K., De, B. J., Lukas, L., and Vandewalle, J., "Weighted Least Squares Support Vector Machines: Robustness and Sparse Approximation," Neurocomput, Vol. 48, Nos. 1-4, 2002, pp. 85-105.   DOI   ScienceOn
9 Bazant, Z. P. and Kazemi, M. T., "Determination of Fracture Energy, Process Zone Length and Brittleness Number from Size Effect with Application to Rock and Concrete," XInt, J. Fract, Vol. 44, No. 2, 1990, pp. 111-131.   DOI
10 Bazant, Z. P. and Oh, B. H., "Crack Band Theory for Fracture Concrete," Mater. Struct. (RILEM), Vol. 16, No. 93, 1983, pp. 155-157.
11 Hillerborg, A., Modeer, M., and Petersson, P. E., "Analysis of Crack Formation and Crack Growth in Concrete by Means of Fracture Mechanics and Finite Elements," Cem. Conc., Vol. 6, 1976, pp. 773-782.   DOI   ScienceOn
12 Jenq, Y. S. and Shah, S. P., "Two-Parameter Fracture Model for Concrete," ASCE J. Engr. Mech., Vol. 111, No. 10, 1985, pp. 1227-1241.   DOI   ScienceOn
13 John, Y. S. and Shah, S. P., "Fracture Mechanics Analysis of High Strength Concrete," ASCE J. Mater. Civil. Engr., Vol. 1, No. 4, 1989, pp. 185-198.   DOI
14 Tang, T., Ouyang, C., and Shah, S. P., "A Simple Method for Determining Material Fracture Parameters from Peak Loads," ACI Mater. J., Vol. 93, No. 2, 1996, pp. 147-157.