hrcak mascot   Srce   HID

Izvorni znanstveni članak
https://doi.org/10.17559/TV-20200422014902

Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network

Mert Alkan ; Burdur Mehmet Akif Ersoy University, Faculty of Engineering and Architecture, 15550 Burdur, Turkey
Hüseyin Hakan Ince ; Burdur Mehmet Akif Ersoy University, Faculty of Engineering and Architecture, 15550 Burdur, Turkey
Melda Alkan Çakiroğlu ; Department of Civil Engineering, Isparta University of Applied Sciences, 32200 Isparta, Turkey
Ahmet Ali Süzen*   ORCID icon orcid.org/0000-0002-5871-1652 ; Department of Information Security Technology, Isparta University of Applied Sciences, 32050 Isparta, Turkey

Puni tekst: engleski, pdf (2 MB) str. 426-432 preuzimanja: 27* citiraj
APA 6th Edition
Alkan, M., Ince, H.H., Çakiroğlu, M.A. i Süzen*, A.A. (2021). Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network. Tehnički vjesnik, 28 (2), 426-432. https://doi.org/10.17559/TV-20200422014902
MLA 8th Edition
Alkan, Mert, et al. "Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network." Tehnički vjesnik, vol. 28, br. 2, 2021, str. 426-432. https://doi.org/10.17559/TV-20200422014902. Citirano 12.05.2021.
Chicago 17th Edition
Alkan, Mert, Hüseyin Hakan Ince, Melda Alkan Çakiroğlu i Ahmet Ali Süzen*. "Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network." Tehnički vjesnik 28, br. 2 (2021): 426-432. https://doi.org/10.17559/TV-20200422014902
Harvard
Alkan, M., et al. (2021). 'Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network', Tehnički vjesnik, 28(2), str. 426-432. https://doi.org/10.17559/TV-20200422014902
Vancouver
Alkan M, Ince HH, Çakiroğlu MA, Süzen* AA. Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network. Tehnički vjesnik [Internet]. 2021 [pristupljeno 12.05.2021.];28(2):426-432. https://doi.org/10.17559/TV-20200422014902
IEEE
M. Alkan, H.H. Ince, M.A. Çakiroğlu i A.A. Süzen*, "Prediction of Rebound Amount in Dry Mix Shotcrete by a Fast Adaboosting Neural Network", Tehnički vjesnik, vol.28, br. 2, str. 426-432, 2021. [Online]. https://doi.org/10.17559/TV-20200422014902

Sažetak
In this study, a new machine learning approach has been proposed to predict the rebound causing loss of material in shotcrete using the ensemble learning method. In shotcrete application, the amount of rebound material was obtained for use in a dataset. In this study, the shotcrete mixes that contain an additive of fly-ash, silica fume, and polypropylene fiber were produced besides simple shotcrete. Each mix was sprayed onto 2 wooden panels measuring 45 × 45 × 15 cm in size. The rebound material resulting from the spraying process was collected, weighed and recorded as data. The highest rebound was observed for the plain sample and the lowest for samples with substituted silica fume. Dependent and independent parameters were identified in the dataset produced as a result of experimental studies. Hyperparameters producing optimum results in the training of the model were identified for the model and boosting method. The dataset was split into training and testing sets by 80% and 20%, respectively. As a result, the model achieved a prediction performance of 84.25%. To test the performance of the proposed model, traditional machine learning algorithms were compared on the same dataset. Consequently, the proposed model was observed to have the highest accuracy.

Ključne riječi
adaboosting; dry-mix shotcrete; ensemble learning; neural network; rebound

Hrčak ID: 255808

URI
https://hrcak.srce.hr/255808

Posjeta: 69 *