Estimation of specific gravity with penetration and penetration index parameters by artificial neural network
Periodicals of Engineering and Natural Sciences, vol.5, no.2, pp.161-164, 2017 (Scopus)
- Publication Type: Article / Article
- Volume: 5 Issue: 2
- Publication Date: 2017
- Doi Number: 10.21533/pen.v5i2.106
- Journal Name: Periodicals of Engineering and Natural Sciences
- Journal Indexes: Scopus
- Page Numbers: pp.161-164
- Keywords: Artifical neural network, Penetration, Penetration index, Specific gravity
- Isparta University of Applied Sciences Affiliated: No
Abstract
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.