Determination of the resistance characteristics of self-compacting concrete samples by Artificial Neural Network
Yazarlar (6)
Arş. Gör. Mustafa Altin Selçuk Üniversitesi, Türkiye
Prof. Dr. Ismail Saritas Selçuk Üniversitesi, Türkiye
M. Tolga Cogurcu
Selçuk Üniversitesi, Türkiye
Selçuk Üniversitesi, Türkiye
Prof. Dr. Şakir TAŞDEMİR Selçuk Üniversitesi, Türkiye
Prof. Dr. Mehmet Kamanli Selçuk Üniversitesi, Türkiye
M. Yasar Kaltakci Selçuk Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | |||
| DOI Numarası | 10.1145/1500879.1500924 | ||
| Kongre Adı | Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for Phd Students in Computing Compsystech 08 | ||
| Kongre Tarihi | / | ||
| Basıldığı Ülke | Basıldığı Şehir | ||
| Bildiri Linki | https://dl.acm.org/doi/abs/10.1145/1500879.1500924 | ||
| UAK Araştırma Alanları |
Mühendislik
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| Özet |
| In this study, in order to determine the resistance characteristics of self-compacting concrete (SCC) samples, experiments were done in the Konya Cement Factory, Ready-mix Concrete Establishment. Four different mixture proportions were chosen in the experimental study. 24 samples of the 4 mixtures were selected in order to set the cube compression strength. For each mixture, these 24 samples were broken down within 28 days and the characteristics of cube compression strength were obtained. After 28 days, compression strength average was found to be 50.0300 MPa. A model of Artificial Neural Network (ANN) was designed for this study and the results were obtained in this model of ANN. Both experimental and ANN data was analyzed with SPSS statistical packet software. The result of statistical analysis (p=0.9972) has been done in 95% of confidence interval. It has been seen that the ANN can be used … |
| Anahtar Kelimeler |
| Artificial Neural Network | Compressive strength | Self compacting concrete (SCC) |
| Atıf Sayıları | |
| Scopus | 1 |
| Google Scholar | 3 |