Title

Neural Networks Applications in Pavement Engineering: A Recent Survey

Document Type

Article

Publication Date

11-2014

Journal or Book Title

International Journal of Pavement Research and Technology

Volume

7

Issue

6

First Page

434

Last Page

444

DOI

10.6135/ijprt.org.tw/2014.7(6).434

Abstract

The use of neural networks (NNs) has increased tremendously in several areas of engineering over the last three decades. This paper is intended to provide a state-of-the-art survey of NN applications in pavement engineering over the last three decades. The reported studies are briefly summarized under eight different categories: (1) prediction of pavement condition and performance, (2) pavement management and maintenance strategies, (3) pavement distress forecasting, (4) structural evaluation of pavement systems, (5) pavement image analysis and classification, (6) pavement materials modeling, and (7) other miscellaneous transportation infrastructure applications. To maintain consistency, the review was primarily based on archival journal publications although novel application-oriented NN implementations published in peer-reviewed conference proceedings and edited books were also considered. Recent publications focusing on the development and use of hybrid neural systems in pavement engineering were also included in the review. The increasing number of publications in this area of research in combination with other soft computing techniques every year definitely indicates that more and more students, researchers, and practitioners are interested in exploring the use of NNs in the study of pavement engineering problems.

Research Focus Area

Transportation Engineering

Comments

This is an article from International Journal of Pavement Research and Technology 7 (2014): 434, doi: 10.6135/ijprt.org.tw/2014.7(6).434. Posted with permission.

Copyright Owner

Chinese Society of Pavement Engineering

Language

en

File Format

application/pdf

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