Journal of Materials and Engineering Structures
Volume 6, Numéro 1, Pages 93-103

Enhanced Soft Computing For Ensemble Approach To Estimate The Compressive Strength Of High Strength Concrete

Authors : Sihag Parveen . Kumar Munish . Singh Varun .


High strength concrete (HCS) define as the concrete that meets unique mixture of performance uniformity requirements that cannot be reached routinely using conventional constituents and regular mixing, placing, and curing events. The modeling of such type of concrete is very difficult. In this investigation, the performance of the gaussian process (GP) regression, support vector Machine (SVM) and artificial neural network (ANN) were compared to estimate the 28th day compressive strength of the HSC. Total data set consists of 83 data out of which 70 % of total dataset used to train the model and residual 30% used to test the models. The model accuracy was depend upon the five performance evaluation parameter which were correlation coefficient (R), Bias, mean square error (MAE), root mean square error (RMSE) and Nash-Sutcliffe model efficiency (E). The results recommend that ANN model is more accurate to predict the compressive strength as compare to GP and SVM based models. Sensitivity analysis indicated that Cement (C), Silica fume (SF), Fly ash (FA) and Water (W) are the most valuable constituents in which compressive strength of the HCS is mainly depend for this data set.


High strength concretes; Gaussian process; Support vectors Machine; artificial neural network

Estimation Of Compressive Strength Of High-strength Concrete By Random Forest And M5p Model Tree Approaches

Singh Balraj .  Sihag Parveen .  Tomar Anjul .  Sehgad Ankush . 
pages 583-892.

Workability, Compressive Strength And Initial Surface Absorption Of Laterized Concrete

Folagbade Samuel Olufemi .  Osadola Opeyemi Ayodeji . 
pages 455-463.

Effect Of Different Curing Methods On The Compressive Strength Development Of Pulverized Copper Slag Concrete

Boakye Daniel M. .  Uzoegbo Herbert C. .  Mojagotlhe Nonhlanhla .  Malemona Moeti . 
pages 11-21.