| dc.contributor.author | Demir, A. and Kumanlioglu, A.A. | |
| dc.date.accessioned | 2020-07-02T07:11:04Z | |
| dc.date.available | 2020-07-02T07:11:04Z | |
| dc.date.issued | 2017 | |
| dc.identifier.citation | cited By 0 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013628827&doi=10.1063%2f1.4972637&partnerID=40&md5=3ef7232d7a0656487d94455bc0a186bc | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12481/12197 | |
| dc.description.abstract | The aim of this study is to predict with Artificial Neural Networks (ANN) shear strength of brick masonry walls. Shear strength of the walls is determined with diagonal shear tests. It is very difficult to determine strengths of brick masonry walls with experimental procedures. Therefore, an Artificial Neural Networks model is developed with data obtained by investigating many papers from literature and experiments carried out by the authors. Finally, a good degree of coherency is obtained between the experimental and predicted data. The model that is developed makes it possible to easily predict shear strength of the masonry walls. Additionally, this model can be continuously trained with new data and its applicability range can easily be expanded. © 2017 Author(s). | |
| dc.language.iso | English | |
| dc.publisher | American Institute of Physics Inc. | |
| dc.title | The prediction of brick wall strengths with artificial neural networks model | |
| dc.type | Conference Paper | |
| dc.contributor.department | Department of Civil Engineering, Engineering Faculty, Celal Bayar University, Manisa, 45140, Turkey | |
| dc.identifier.DOI-ID | 10.1063/1.4972637 | |
| dc.identifier.volume | 1798 | |
