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The Scientific World Journal
Volume 2014, Article ID 515467, 16 pages
http://dx.doi.org/10.1155/2014/515467
Research Article

Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN

Department of Civil Engineering, K.N.Toosi University of Technology, No. 1346, Vali Asr Street, Mirdamad Intersection, Tehran 19967-15433, Iran

Received 25 August 2013; Accepted 24 October 2013; Published 4 February 2014

Academic Editors: N. Avdelidis and J. Zheng

Copyright © 2014 Ali Reza Ghanizadeh and Mansour Fakhri. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [1 citation]

The following is the list of published articles that have cited the current article.

  • Fabricio Leiva-Villacorta, Adriana Vargas-Nordcbeck, and David H. Timm, “Non-destructive evaluation of sustainable pavement technologies using artificial neural networks,” International Journal of Pavement Research and Technology, vol. 10, no. 2, pp. 139–147, 2017. View at Publisher · View at Google Scholar