Estimation of specific gravity with penetration and penetration index parameters by artificial neural network

Sercan Serin, Sebnem Karahancer, Ekinhan Eriskin, Nihat Morova, Mehmet Saltan, Serdal Terzi

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.

Keywords


Artifical neural network; spesific gravity; penetration; penetration index

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DOI: http://dx.doi.org/10.21533/pen.v5i2.106

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Copyright (c) 2017 Periodicals of Engineering and Natural Sciences (PEN)

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ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License