Artificial intelligence approach for predicting compressive strength of foamed concrete
Accurately predicting the compressive strength of foamed concrete plays a key role in the wide application of foamed concrete in practice. This study investigates the performance of the six AI models in estimating the compressive strength of foamed concrete. A dataset of 150 samples available in the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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The University of Danang
2024-03-01
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| Series: | Tạp chí Khoa học và Công nghệ |
| Subjects: | |
| Online Access: | https://jst-ud.vn/jst-ud/article/view/8986 |
| _version_ | 1827281413393612800 |
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| author | Nguyen Thi Loc Mai Anh Duc Nguyen Cong Luyen Vu Huy Cong Nguyen Van Huong |
| author_facet | Nguyen Thi Loc Mai Anh Duc Nguyen Cong Luyen Vu Huy Cong Nguyen Van Huong |
| author_sort | Nguyen Thi Loc |
| collection | DOAJ |
| description | Accurately predicting the compressive strength of foamed concrete plays a key role in the wide application of foamed concrete in practice. This study investigates the performance of the six AI models in estimating the compressive strength of foamed concrete. A dataset of 150 samples available in the literature was used for training and testing the AI models. The dry density, cement and sand content, and water-to-cement ratio were employed as input parameters, while the 28-day compressive strength was used as the output parameter. Four statistical indicators were utilized to evaluate the performance of the AI models. The study results reveal that the AI models yield an accurate prediction of the compressive strength of foamed concrete. The best performance model in estimating the compressive strength of foamed concrete is the M5Rules model, while the least accurate model depends on the indicators used to measure the accuracy of the AI models. |
| first_indexed | 2024-04-24T09:00:33Z |
| format | Article |
| id | doaj.art-3d3338d097d8482d9dfc5293d1a701db |
| institution | Directory Open Access Journal |
| issn | 1859-1531 |
| language | English |
| last_indexed | 2024-04-24T09:00:33Z |
| publishDate | 2024-03-01 |
| publisher | The University of Danang |
| record_format | Article |
| series | Tạp chí Khoa học và Công nghệ |
| spelling | doaj.art-3d3338d097d8482d9dfc5293d1a701db2024-04-16T01:31:57ZengThe University of DanangTạp chí Khoa học và Công nghệ1859-15312024-03-01131910.31130/ud-jst.2024.013E8980Artificial intelligence approach for predicting compressive strength of foamed concreteNguyen Thi Loc0Mai Anh Duc1Nguyen Cong Luyen2Vu Huy Cong3Nguyen Van Huong4Central College of Transport V, Danang, VietnamThe University of Danang - University of Science and Technology, Danang, VietnamThe University of Danang - University of Science and Technology, Danang, VietnamThe University of Danang - University of Science and Technology, Danang, VietnamThe University of Danang - University of Science and Technology, Danang, VietnamAccurately predicting the compressive strength of foamed concrete plays a key role in the wide application of foamed concrete in practice. This study investigates the performance of the six AI models in estimating the compressive strength of foamed concrete. A dataset of 150 samples available in the literature was used for training and testing the AI models. The dry density, cement and sand content, and water-to-cement ratio were employed as input parameters, while the 28-day compressive strength was used as the output parameter. Four statistical indicators were utilized to evaluate the performance of the AI models. The study results reveal that the AI models yield an accurate prediction of the compressive strength of foamed concrete. The best performance model in estimating the compressive strength of foamed concrete is the M5Rules model, while the least accurate model depends on the indicators used to measure the accuracy of the AI models.https://jst-ud.vn/jst-ud/article/view/8986compressive strength of foamed concreteartificial intelligence modelsprediction of the compressive strength of foamed concrete |
| spellingShingle | Nguyen Thi Loc Mai Anh Duc Nguyen Cong Luyen Vu Huy Cong Nguyen Van Huong Artificial intelligence approach for predicting compressive strength of foamed concrete Tạp chí Khoa học và Công nghệ compressive strength of foamed concrete artificial intelligence models prediction of the compressive strength of foamed concrete |
| title | Artificial intelligence approach for predicting compressive strength of foamed concrete |
| title_full | Artificial intelligence approach for predicting compressive strength of foamed concrete |
| title_fullStr | Artificial intelligence approach for predicting compressive strength of foamed concrete |
| title_full_unstemmed | Artificial intelligence approach for predicting compressive strength of foamed concrete |
| title_short | Artificial intelligence approach for predicting compressive strength of foamed concrete |
| title_sort | artificial intelligence approach for predicting compressive strength of foamed concrete |
| topic | compressive strength of foamed concrete artificial intelligence models prediction of the compressive strength of foamed concrete |
| url | https://jst-ud.vn/jst-ud/article/view/8986 |
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