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Bhairevi Ganesh Aiyer,김두기,Nithin Karingattikka,Pijush Samui,P. Ramamohan Rao 대한토목학회 2014 KSCE Journal of Civil Engineering Vol.18 No.6
This article examines the capability of Least Square Support Vector Machine (LSSVM) and Relevance Vector Machine (RVM) fordetermination of compressive strength (fc) of self compacting concrete. The input variables of LSSVM and RVM are Cement (kg/m3)(C),Fly ash (kg/m3)(F), Water/powder (w/p), Superplasticizer dosage (%)(SP) Sand (kg/m3)(S) and Coarse Aggregate (kg/m3)(CA). Theoutput of LSSVM and RVM is fc. The developed LSSVM and RVM give equations for prediction of fc. A comparative study has beendone between the developed LSSVM, RVM and ANN models. Experiments have been conducted to verify the developed RVM andLSSVM. The developed RVM gives variance of the predicted fc. The results confirm that the developed RVM is a robust model forprediction of fc of self compacting concrete.