Name
Title | ||
|---|---|---|
A new predictive model for compressive strength of HPC using gene expression programming |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.advengsoft.2011.09.014 | Advances in Engineering Software |
Keywords | Field | DocType |
gene expression programming,new predictive model,sensitivity analysis,new model,gep model,high performance concrete,squares regression analysis,optimal gep model,prediction performance,compressive strength,regression model,regression analysis,prediction | Gene expression programming,Regression,Computer science,Regression analysis,Compressive strength,Non-linear least squares,High performance concrete,Structural engineering | Journal |
Volume | Issue | ISSN |
45 | 1 | 0965-9978 |
Citations | PageRank | References |
12 | 0.78 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seyyed Mohammad Mousavi | 1 | 25 | 2.27 |
| Pejman Aminian | 2 | 27 | 2.46 |
| Amir Hossein Gandomi | 3 | 1836 | 110.25 |
| Amir Hossein Alavi | 4 | 1016 | 45.59 |
| Hamed Bolandi | 5 | 12 | 0.78 |