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

Citation