Estimation of specific gravity with penetration and penetration index parameters by artificial neural network
Periodicals of Engineering and Natural Sciences, cilt.5, sa.2, ss.161-164, 2017 (Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 5 Sayı: 2
- Basım Tarihi: 2017
- Doi Numarası: 10.21533/pen.v5i2.106
- Dergi Adı: Periodicals of Engineering and Natural Sciences
- Derginin Tarandığı İndeksler: Scopus
- Sayfa Sayıları: ss.161-164
- Anahtar Kelimeler: Artifical neural network, Penetration, Penetration index, Specific gravity
- Isparta Uygulamalı Bilimler Üniversitesi Adresli: Hayır
Özet
Specific Gravity of the bitumen changes according to the ambient temperature. Different specific gravity values can be calculated at different temperature. Estimating models like Artificial Neural Network - ANN could be very useful to obtain the specific gravity value uniform. Specific gravity values obtained from Long-Term Pavement Performance - LTPP were estimated with artificial neural networks. Penetration and Penetration Index of binder were used for estimating the specific gravity of the bitumen. As a result, ANN get 84% of R2 between obtained and estimated values.