| Yazarlar (1) |
Prof. Dr. Mahmut BİLGEHAN
Kastamonu Üniversitesi, Türkiye |
| Özet |
| In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) model have been successfully used for the evaluation of relationships between concrete compressive strength and ultrasonic pulse velocity (UPV) values using the experimental data obtained from many cores taken from different reinforced concrete structures having different ages and unknown ratios of concrete mixtures. A comparative study is made using the neural nets and neuro-fuzzy (NF) techniques. Statistic measures were used to evaluate the performance of the models. Comparing of the results, it is found that the proposed ANFIS architecture with Gaussian membership function is found to perform better than the multilayer feed-forward ANN learning by backpropagation algorithm. The final results show that especially the ANFIS modelling may constitute an efficient tool for prediction of the concrete compressive … |
| Anahtar Kelimeler |
| ultrasonic pulse velocity,compressive strength,ANFIS,ANN |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Nondestructive Testing and Evaluation |
| Dergi ISSN | 1058-9759 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Makale Dili | İngilizce |
| Basım Tarihi | 03-2011 |
| Cilt No | 26 |
| Sayı | 1 |
| Sayfalar | 35 / 55 |
| Doi Numarası | 10.1080/10589751003770100 |
| Makale Linki | http://www.tandfonline.com/doi/abs/10.1080/10589751003770100 |
| Atıf Sayıları | |
| Google Scholar | 82 |
