G. Jayaprakash1, M. P. Muthuraj2,*
CMC-Computers, Materials & Continua, Vol.54, No.1, pp. 83-102, 2018, DOI:10.3970/cmc.2018.054.083
Abstract This paper discusses the applicability of relevance vector machine (RVM) based regression to predict the compressive strength of various self compacting concrete (SCC) mixes. Compressive strength data various SCC mixes has been consolidated by considering the effect of water cement ratio, water binder ratio and steel fibres. Relevance vector machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM has an identical functional form to the support vector machine, but provides probabilistic classification and regression. RVM is based on a Bayesian formulation of a More >
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