Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming
One of the problems of optimization of concrete is to formulate a mathematical equation that shows the relationship between the various constituents of concrete and its properties. In this work, modelling of the compressive strength of concrete admixed with metakaolin was carried out using the Gene...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8883412 |
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| author | Oluwatobi O. Akin Amana Ocholi Olugbenga S. Abejide Johnson A. Obari |
| author_facet | Oluwatobi O. Akin Amana Ocholi Olugbenga S. Abejide Johnson A. Obari |
| author_sort | Oluwatobi O. Akin |
| collection | DOAJ |
| description | One of the problems of optimization of concrete is to formulate a mathematical equation that shows the relationship between the various constituents of concrete and its properties. In this work, modelling of the compressive strength of concrete admixed with metakaolin was carried out using the Gene Expression Programming (GEP) algorithm. The dataset from laboratory experimentation was used for the analysis. The mixture proportions were made of three different water/binder ratios (0.4, 0.5, and 0.6), and the grades of concrete produced were grade M15 and M20. The compressive strength of the concrete was determined after 28 days of curing. The parameters used in the GEP algorithm are the input variables which include cement content, water, metakaolin content, and fine and coarse aggregate, while the response was designated as the compressive strength. The model was trained and tested using the parameters. The R-square value from the GEP algorithm was compared with the use of conventional stepwise regression analysis. With a coefficient of determination (R-square value) of 0.95, the GEP algorithm has shown to be a good alternative for modelling concrete compressive strength. |
| format | Article |
| id | doaj-art-b010c9474ae849738ede13f6bef7d54e |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-b010c9474ae849738ede13f6bef7d54e2025-02-03T06:46:47ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88834128883412Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression ProgrammingOluwatobi O. Akin0Amana Ocholi1Olugbenga S. Abejide2Johnson A. Obari3Department of Civil Engineering, Ahmadu Bello University, Zaria, NigeriaDepartment of Civil Engineering, Ahmadu Bello University, Zaria, NigeriaDepartment of Civil Engineering, Ahmadu Bello University, Zaria, NigeriaDepartment of Electrical and Computer Engineering, Ahmadu Bello University, Zaria, NigeriaOne of the problems of optimization of concrete is to formulate a mathematical equation that shows the relationship between the various constituents of concrete and its properties. In this work, modelling of the compressive strength of concrete admixed with metakaolin was carried out using the Gene Expression Programming (GEP) algorithm. The dataset from laboratory experimentation was used for the analysis. The mixture proportions were made of three different water/binder ratios (0.4, 0.5, and 0.6), and the grades of concrete produced were grade M15 and M20. The compressive strength of the concrete was determined after 28 days of curing. The parameters used in the GEP algorithm are the input variables which include cement content, water, metakaolin content, and fine and coarse aggregate, while the response was designated as the compressive strength. The model was trained and tested using the parameters. The R-square value from the GEP algorithm was compared with the use of conventional stepwise regression analysis. With a coefficient of determination (R-square value) of 0.95, the GEP algorithm has shown to be a good alternative for modelling concrete compressive strength.http://dx.doi.org/10.1155/2020/8883412 |
| spellingShingle | Oluwatobi O. Akin Amana Ocholi Olugbenga S. Abejide Johnson A. Obari Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming Advances in Civil Engineering |
| title | Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming |
| title_full | Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming |
| title_fullStr | Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming |
| title_full_unstemmed | Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming |
| title_short | Prediction of the Compressive Strength of Concrete Admixed with Metakaolin Using Gene Expression Programming |
| title_sort | prediction of the compressive strength of concrete admixed with metakaolin using gene expression programming |
| url | http://dx.doi.org/10.1155/2020/8883412 |
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