Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression Programming
Several studies have established that strength development in concrete is not only determined by the water/binder ratio, but it is also affected by the presence of other ingredients. With the increase in the number of concrete ingredients from the conventional four materials by addition of various t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Pouyan Press
2019-04-01
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| Series: | Journal of Soft Computing in Civil Engineering |
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| Online Access: | http://www.jsoftcivil.com/article_91665_15e2d18e860a8f0d9168e8706f0fb03b.pdf |
| _version_ | 1818570330981007360 |
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| author | Oluwatobi Akin Olugbenga Abejide |
| author_facet | Oluwatobi Akin Olugbenga Abejide |
| author_sort | Oluwatobi Akin |
| collection | DOAJ |
| description | Several studies have established that strength development in concrete is not only determined by the water/binder ratio, but it is also affected by the presence of other ingredients. With the increase in the number of concrete ingredients from the conventional four materials by addition of various types of admixtures (agricultural wastes, chemical, mineral and biological) to achieve a desired property, modelling its behavior has become more complex and challenging. Presented in this work is the possibility of adopting the Gene Expression Programming (GEP) algorithm to predict the compressive strength of concrete admixed with Ground Granulated Blast Furnace Slag (GGBFS) as Supplementary Cementitious Materials (SCMs). A set of data with satisfactory experimental results were obtained from literatures for the study. Result from the GEP algorithm was compared with that from stepwise regression analysis in order to appreciate the accuracy of GEP algorithm as compared to other data analysis program. With R-Square value and MSE of -0.94 and 5.15 respectively, The GEP algorithm proves to be more accurate in the modelling of concrete compressive strength. |
| first_indexed | 2024-12-14T11:59:04Z |
| format | Article |
| id | doaj.art-f9bebd908e7944399783ea5e54702049 |
| institution | Directory Open Access Journal |
| issn | 2588-2872 2588-2872 |
| language | English |
| last_indexed | 2024-12-14T11:59:04Z |
| publishDate | 2019-04-01 |
| publisher | Pouyan Press |
| record_format | Article |
| series | Journal of Soft Computing in Civil Engineering |
| spelling | doaj.art-f9bebd908e7944399783ea5e547020492022-12-21T23:02:02ZengPouyan PressJournal of Soft Computing in Civil Engineering2588-28722588-28722019-04-0132435310.22115/scce.2019.178214.110391665Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression ProgrammingOluwatobi Akin0Olugbenga Abejide1Postgraduate Student, Department of Civil Engineering, Ahmadu Bello University, Zaria, NigeriaProfessor, Department of Civil Engineering, Ahmadu Bello University, Zaria, NigeriaSeveral studies have established that strength development in concrete is not only determined by the water/binder ratio, but it is also affected by the presence of other ingredients. With the increase in the number of concrete ingredients from the conventional four materials by addition of various types of admixtures (agricultural wastes, chemical, mineral and biological) to achieve a desired property, modelling its behavior has become more complex and challenging. Presented in this work is the possibility of adopting the Gene Expression Programming (GEP) algorithm to predict the compressive strength of concrete admixed with Ground Granulated Blast Furnace Slag (GGBFS) as Supplementary Cementitious Materials (SCMs). A set of data with satisfactory experimental results were obtained from literatures for the study. Result from the GEP algorithm was compared with that from stepwise regression analysis in order to appreciate the accuracy of GEP algorithm as compared to other data analysis program. With R-Square value and MSE of -0.94 and 5.15 respectively, The GEP algorithm proves to be more accurate in the modelling of concrete compressive strength.http://www.jsoftcivil.com/article_91665_15e2d18e860a8f0d9168e8706f0fb03b.pdfconcretestrengthggbfsgep |
| spellingShingle | Oluwatobi Akin Olugbenga Abejide Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression Programming Journal of Soft Computing in Civil Engineering concrete strength ggbfs gep |
| title | Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression Programming |
| title_full | Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression Programming |
| title_fullStr | Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression Programming |
| title_full_unstemmed | Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression Programming |
| title_short | Modelling of Concrete Compressive Strength Admixed with GGBFS Using Gene Expression Programming |
| title_sort | modelling of concrete compressive strength admixed with ggbfs using gene expression programming |
| topic | concrete strength ggbfs gep |
| url | http://www.jsoftcivil.com/article_91665_15e2d18e860a8f0d9168e8706f0fb03b.pdf |
| work_keys_str_mv | AT oluwatobiakin modellingofconcretecompressivestrengthadmixedwithggbfsusinggeneexpressionprogramming AT olugbengaabejide modellingofconcretecompressivestrengthadmixedwithggbfsusinggeneexpressionprogramming |