Journal
ADVANCES IN ENGINEERING SOFTWARE
Volume 45, Issue 1, Pages 105-114Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.advengsoft.2011.09.014
Keywords
High performance concrete; Gene expression programming; Compressive strength; Regression analysis; Sensitivity analysis; Prediction
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In this study, gene expression programming (GEP) is utilized to derive a new model for the prediction of compressive strength of high performance concrete (HPC) mixes. The model is developed using a comprehensive database obtained from the literature. The validity of the proposed model is verified by applying it to estimate the compressive strength of a portion of test results that are not included in the analysis. Linear and nonlinear least squares regression analyses are performed to benchmark the GEP model. Contributions of the parameters affecting the compressive strength are evaluated through a sensitivity analysis. GEP is found to be an effective method for evaluating the compressive strength of HPC mixes. The prediction performance of the optimal GEP model is better than the regression models. (C) 2011 Elsevier Ltd. All rights reserved.
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