Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond
Fiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/12/6955 |
| _version_ | 1827738760178040832 |
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| author | Reza Kamgar Houman Ebrahimpour Komleh Anna Jakubczyk-Gałczyńska Robert Jankowski |
| author_facet | Reza Kamgar Houman Ebrahimpour Komleh Anna Jakubczyk-Gałczyńska Robert Jankowski |
| author_sort | Reza Kamgar |
| collection | DOAJ |
| description | Fiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of FRP strips applied on masonry substrates. The results obtained via ANN, KFCV, MARS, and M5MT were compared with the existing models. The results clearly indicate that the considered approaches have better efficiency and higher precision compared to the models available in the literature. The correlation coefficient values for the considered models (i.e., ANN, KFCV, MARS, and M5MT) are promising results, with up to 99% reliability. |
| first_indexed | 2024-03-11T02:48:52Z |
| format | Article |
| id | doaj.art-8f1502028b9840fe83be66f9057eeb81 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T02:48:52Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-8f1502028b9840fe83be66f9057eeb812023-11-18T09:06:55ZengMDPI AGApplied Sciences2076-34172023-06-011312695510.3390/app13126955Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates BondReza Kamgar0Houman Ebrahimpour Komleh1Anna Jakubczyk-Gałczyńska2Robert Jankowski3Department of Civil Engineering, Faculty of Engineering, Shahrekord University, Shahrekord 88186-34141, IranDepartment of Civil Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman 76169-13439, IranFaculty of Civil and Environmental Engineering, Gdansk University of Technology, 80-233 Gdansk, PolandFaculty of Civil and Environmental Engineering, Gdansk University of Technology, 80-233 Gdansk, PolandFiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of FRP strips applied on masonry substrates. The results obtained via ANN, KFCV, MARS, and M5MT were compared with the existing models. The results clearly indicate that the considered approaches have better efficiency and higher precision compared to the models available in the literature. The correlation coefficient values for the considered models (i.e., ANN, KFCV, MARS, and M5MT) are promising results, with up to 99% reliability.https://www.mdpi.com/2076-3417/13/12/6955Fiber-Reinforced PolymersArtificial Neural NetworkK-fold Cross-ValidationMultivariate Adaptive Regression SplineM5 Model Tree |
| spellingShingle | Reza Kamgar Houman Ebrahimpour Komleh Anna Jakubczyk-Gałczyńska Robert Jankowski Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond Applied Sciences Fiber-Reinforced Polymers Artificial Neural Network K-fold Cross-Validation Multivariate Adaptive Regression Spline M5 Model Tree |
| title | Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond |
| title_full | Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond |
| title_fullStr | Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond |
| title_full_unstemmed | Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond |
| title_short | Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond |
| title_sort | estimation of the ultimate strength of frp strips to masonry substrates bond |
| topic | Fiber-Reinforced Polymers Artificial Neural Network K-fold Cross-Validation Multivariate Adaptive Regression Spline M5 Model Tree |
| url | https://www.mdpi.com/2076-3417/13/12/6955 |
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