Utilisation of Artificial Neural Network for the Analysis of Interlayer Shear Properties
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.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/1822427X
-
Authors:
- Raab, Christiane
- El Halim, Abd El Halim Omar Abd
- Part, Manfred Norbert
- Publication Date: 2013
Language
- English
Media Info
- Media Type: Print
- Features: Figures; Maps; References; Tables;
- Pagination: pp 107-116
-
Serial:
- Baltic Journal of Road and Bridge Engineering
- Volume: 8
- Issue Number: 2
- Publisher: Vilnius Gediminas Technical University
- ISSN: 1822-427X
- EISSN: 1822-4288
- Serial URL: https://bjrbe-journals.rtu.lv/index
-
Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Bonding and joining; Highway engineering; Neural networks; Pavement design; Pavement interlayers; Pavement layers; Shear stress; Stiffness
- Subject Areas: Data and Information Technology; Design; Highways; Pavements; I22: Design of Pavements, Railways and Guideways; I30: Materials;
Filing Info
- Accession Number: 01493541
- Record Type: Publication
- Files: TRIS
- Created Date: Sep 20 2013 4:26PM