Estimation of specific gravity with penetration and penetration index parameters by artificial neural network
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
International University of Sarajevo
Access Rights
info:eu-repo/semantics/openAccess
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.
Description
Keywords
Artifical neural network; Penetration; Penetration index; Specific gravity
Journal or Series
Periodicals of Engineering and Natural Sciences
WoS Q Value
Scopus Q Value
Q2
Volume
5
Issue
2
