Christiane Raab, Abd El Halim Omar Abd El Halim, Manfred Norbert Part - Utilisation of artificial neural network for the analysis of interlayer shear properties (Vol VIII, No 2)

Vilnius Gediminas Technical UniversityRiga Technical UniversityTallinn University of TechnologyBaltic Road Association

 

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2015 Impact Factor: 0.519 ©2015 Thomson Reuters, 2015 Journal Citation Report®

ISSN 1822-427X print
ISSN 1822-4288 online
 

 

 
 

"The Baltic Journal of Road and Bridge Engineering"
Vilnius: Technika, 2013, Vol VIII, No 2, p. 107-116


Christiane Raab, Abd El Halim Omar Abd El Halim, Manfred Norbert Part

Utilisation of artificial neural network for the analysis of interlayer shear properties

DOI: 10.3846/bjrbe.2013.14
 
For a long time artificial intelligence tools were not used in pavement engineering, but their application is becoming more and more important. As opposed to other subjects in pavement engineering this is not yet the case for interlayer bonding. The aim of this paper is to apply artificial intelligence in form of artificial neural network for knowledge discovery from pavement engineering data in the field of interlayer bonding. This means that the focus is on practical use of artificial neural network and its application for datasets on interlayer bonding in order to find pattern within the data and to predict certain interlayer bond properties. It was shown that artificial neural network techniques are suitable for deriving models from datasets and to predict interlayer shear bond properties such as max shear force, deformation at max shear stress, and max shear stiffness.
 
Keywords: interlayer bond test devices, artificial neural network (ANN), asphalt pavements.

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