Application of ANN in Pavement Engineering: State-of-Art
Preprints are manuscripts made publicly available before they have been submitted for formal peer review and publication. They might contain new research findings or data. Preprints can be a draft or final version of an author's research but must not have been accepted for publication at the time of submission.
There has been much
discussion about the impact and future of artificial intelligence (AI) in our lives
and future generations. Many experts even believe that AI will “rule” the
world. Artificial Neural Networks (ANN) have provided a convenient and often extremely
accurate solution to problems within all fields, and can be seen as advanced
general-purpose regression models that try to mimic the behavior of the human
brain. The adoption and use of ANN-based methods in the Mechanistic-Empirical
Pavement Design Guide is a clear sign of the successful use of neural nets in
geomechanical and pavement systems. This work aims to provide an extensive and
detailed state-of-the-art of the application of ANN models to pavement
management, materials and design problems. Unlike former review articles
published before 2014, this work is more descriptive and makes the review much
more appealing to the reader by highlighting numerically and/or graphically the
effectiveness and possible drawbacks of each ANN application.