Utilization of support vector machine for prediction of fracture parameters of concrete

Pijush Samui and Dookie Kim

Abstract

This article employs Support Vector Machine (SVM) for determination of fracture parameters critical stress intensity factor (Ksic) and the critical crack tip opening displacement (CTODc) of concrete. SVM that is firmly based on the theory of statistical learning theory, uses regression technique by introducing

Key Words

concrete; fracture mechanics; support vector machine; sensitivity analysis; artificial neural network; two-parameter model.

Address

Pijush Samui: Centre for Disaster Mitigation and Management. VIT University, Vellore-632014, Tamilnadu, India Dookie Kim: Department of Civil Engineering, Kunsan National University, Kunsan, Jeonbuk, South Korea

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