| Makale Türü |
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| Dergi Adı | Journal of Civil Engineering and Management | ||
| Dergi ISSN | 1392-3730 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 02-2015 |
| Cilt / Sayı / Sayfa | 21 / 3 / 261–281 | DOI | 10.3846/13923730.2015.1005021 |
| Makale Linki | http://www.tandfonline.com/doi/abs/10.3846/13923730.2015.1005021 | ||
| UAK Araştırma Alanları |
Betonarme Yapılar
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| Özet |
| Recent development in data processing systems had directed study and research of engineering towards the creation of intelligent systems to evolve models for a wide range of engineering problems. In this respect, several modeling techniques have been created to simulate various civil engineering systems. This study aims to review the studies on support vector machines (SVM) in structural engineering and investigate the usability of this machine learning based approach by providing three case studies focusing on structural engineering problems. Firstly, the concept of SVM is explained and then, the recent studies on the application of SVM in structural engineering are summarized and discussed. Next, we performed three case studies using the experimental studies provided. Applicability of SVM in structural engineering is confirmed by these case studies. The results showed that SVM is superior to various … |
| Anahtar Kelimeler |
| FRP reinforcement | haunched beams | SFRC corbels | statistical learning | structural engineering | support vector machines | ultimate load capacity |
| Atıf Sayıları | |
| Scopus | 123 |
| Google Scholar | 150 |
| Dergi Adı | Journal of Civil Engineering and Management |
| Yayıncı | Vilnius Gediminas Technical University |
| Açık Erişim | Evet |
| ISSN | 1392-3730 |
| E-ISSN | 1822-3605 |
| CiteScore | 6,4 |
| SJR | 0,707 |
| SNIP | 1,196 |