Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete
For the production of geopolymer concrete (GPC), fly-ash (FA) like waste material has been effectively utilized by various researchers. In this paper, the soft computing techniques known as gene expression programming (GEP) are executed to deliver an empirical equation to estimate the compressive st...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Materials |
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| Online Access: | https://www.mdpi.com/1996-1944/14/5/1106 |
| _version_ | 1797395073182203904 |
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| author | Mohsin Ali Khan Adeel Zafar Arslan Akbar Muhammad Faisal Javed Amir Mosavi |
| author_facet | Mohsin Ali Khan Adeel Zafar Arslan Akbar Muhammad Faisal Javed Amir Mosavi |
| author_sort | Mohsin Ali Khan |
| collection | DOAJ |
| description | For the production of geopolymer concrete (GPC), fly-ash (FA) like waste material has been effectively utilized by various researchers. In this paper, the soft computing techniques known as gene expression programming (GEP) are executed to deliver an empirical equation to estimate the compressive strength <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>f</mi><mi>c</mi><mo>′</mo></msubsup></mrow></semantics></math></inline-formula> of GPC made by employing FA. To build a model, a consistent, extensive and reliable data base is compiled through a detailed review of the published research. The compiled data set is comprised of 298 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>f</mi><mi>c</mi><mo>′</mo></msubsup></mrow></semantics></math></inline-formula> experimental results. The utmost dominant parameters are counted as explanatory variables, in other words, the extra water added as percent FA (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>%</mo><msub><mi>E</mi><mi>W</mi></msub></mrow></semantics></math></inline-formula>), the percentage of plasticizer (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>%</mo><mi>P</mi></mrow></semantics></math></inline-formula>), the initial curing temperature (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>T</mi></semantics></math></inline-formula>), the age of the specimen (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>A</mi></semantics></math></inline-formula>), the curing duration (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>t</mi></semantics></math></inline-formula>), the fine aggregate to total aggregate ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>F</mi><mo>/</mo><msub><mi>A</mi><mi>G</mi></msub></mrow></semantics></math></inline-formula>), the percentage of total aggregate by volume (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo> </mo><mo>%</mo><msub><mi>A</mi><mi>G</mi></msub></mrow></semantics></math></inline-formula>), the percent SiO<sub>2</sub> solids to water ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mo>%</mo><mo> </mo></mrow><mi>S</mi><mo>/</mo><mi>W</mi></mrow></semantics></math></inline-formula>) in sodium silicate (Na<sub>2</sub>SiO<sub>3</sub>) solution, the NaOH solution molarity (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>M</mi></semantics></math></inline-formula>), the activator or alkali to FA ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>A</mi><mi>L</mi></msub><mo>/</mo><msub><mi>F</mi><mi>A</mi></msub></mrow></semantics></math></inline-formula>), the sodium oxide (Na<sub>2</sub>O) to water ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><mo>/</mo><mi>W</mi></mrow></semantics></math></inline-formula>) for preparing Na<sub>2</sub>SiO<sub>3</sub> solution, and the Na<sub>2</sub>SiO<sub>3</sub> to NaOH ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>N</mi><mi>s</mi></msub><mo>/</mo><msub><mi>N</mi><mi>o</mi></msub></mrow></semantics></math></inline-formula>). A GEP empirical equation is proposed to estimate the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>f</mi><mi>c</mi><mo>′</mo></msubsup></mrow></semantics></math></inline-formula> of GPC made with FA. The accuracy, generalization, and prediction capability of the proposed model was evaluated by performing parametric analysis, applying statistical checks, and then compared with non-linear and linear regression equations. |
| first_indexed | 2024-03-09T00:29:07Z |
| format | Article |
| id | doaj.art-1eb4bf15fa004ed7a810b82ad6ab3af2 |
| institution | Directory Open Access Journal |
| issn | 1996-1944 |
| language | English |
| last_indexed | 2024-03-09T00:29:07Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Materials |
| spelling | doaj.art-1eb4bf15fa004ed7a810b82ad6ab3af22023-12-11T18:39:13ZengMDPI AGMaterials1996-19442021-02-01145110610.3390/ma14051106Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer ConcreteMohsin Ali Khan0Adeel Zafar1Arslan Akbar2Muhammad Faisal Javed3Amir Mosavi4Department of Structural Engineering, Military College of Engineering (MCE), National University of Science and Technology (NUST), Islamabad 44000, PakistanDepartment of Structural Engineering, Military College of Engineering (MCE), National University of Science and Technology (NUST), Islamabad 44000, PakistanDepartment of Architecture and Civil Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong, ChinaDepartment of Civil Engineering, Comsats University Islamabad, Abbottabad 22060, PakistanFaculty of Civil Engineering, Technische Universität Dresden, 01069 Dresden, GermanyFor the production of geopolymer concrete (GPC), fly-ash (FA) like waste material has been effectively utilized by various researchers. In this paper, the soft computing techniques known as gene expression programming (GEP) are executed to deliver an empirical equation to estimate the compressive strength <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>f</mi><mi>c</mi><mo>′</mo></msubsup></mrow></semantics></math></inline-formula> of GPC made by employing FA. To build a model, a consistent, extensive and reliable data base is compiled through a detailed review of the published research. The compiled data set is comprised of 298 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>f</mi><mi>c</mi><mo>′</mo></msubsup></mrow></semantics></math></inline-formula> experimental results. The utmost dominant parameters are counted as explanatory variables, in other words, the extra water added as percent FA (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>%</mo><msub><mi>E</mi><mi>W</mi></msub></mrow></semantics></math></inline-formula>), the percentage of plasticizer (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>%</mo><mi>P</mi></mrow></semantics></math></inline-formula>), the initial curing temperature (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>T</mi></semantics></math></inline-formula>), the age of the specimen (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>A</mi></semantics></math></inline-formula>), the curing duration (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>t</mi></semantics></math></inline-formula>), the fine aggregate to total aggregate ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>F</mi><mo>/</mo><msub><mi>A</mi><mi>G</mi></msub></mrow></semantics></math></inline-formula>), the percentage of total aggregate by volume (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo> </mo><mo>%</mo><msub><mi>A</mi><mi>G</mi></msub></mrow></semantics></math></inline-formula>), the percent SiO<sub>2</sub> solids to water ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mo>%</mo><mo> </mo></mrow><mi>S</mi><mo>/</mo><mi>W</mi></mrow></semantics></math></inline-formula>) in sodium silicate (Na<sub>2</sub>SiO<sub>3</sub>) solution, the NaOH solution molarity (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>M</mi></semantics></math></inline-formula>), the activator or alkali to FA ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>A</mi><mi>L</mi></msub><mo>/</mo><msub><mi>F</mi><mi>A</mi></msub></mrow></semantics></math></inline-formula>), the sodium oxide (Na<sub>2</sub>O) to water ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><mo>/</mo><mi>W</mi></mrow></semantics></math></inline-formula>) for preparing Na<sub>2</sub>SiO<sub>3</sub> solution, and the Na<sub>2</sub>SiO<sub>3</sub> to NaOH ratio (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>N</mi><mi>s</mi></msub><mo>/</mo><msub><mi>N</mi><mi>o</mi></msub></mrow></semantics></math></inline-formula>). A GEP empirical equation is proposed to estimate the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>f</mi><mi>c</mi><mo>′</mo></msubsup></mrow></semantics></math></inline-formula> of GPC made with FA. The accuracy, generalization, and prediction capability of the proposed model was evaluated by performing parametric analysis, applying statistical checks, and then compared with non-linear and linear regression equations.https://www.mdpi.com/1996-1944/14/5/1106artificial intelligencegene expression programmingfly ashwaste materialsgeopolymerregression analysis |
| spellingShingle | Mohsin Ali Khan Adeel Zafar Arslan Akbar Muhammad Faisal Javed Amir Mosavi Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete Materials artificial intelligence gene expression programming fly ash waste materials geopolymer regression analysis |
| title | Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete |
| title_full | Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete |
| title_fullStr | Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete |
| title_full_unstemmed | Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete |
| title_short | Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete |
| title_sort | application of gene expression programming gep for the prediction of compressive strength of geopolymer concrete |
| topic | artificial intelligence gene expression programming fly ash waste materials geopolymer regression analysis |
| url | https://www.mdpi.com/1996-1944/14/5/1106 |
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