- author = "Mohammadreza R. Mirzahosseini and Amirhossein H. Alavi and Fereidoon {Moghadas Nejad} and Amirhossein H. Gandomi and Mahmoud Ameri",
- title = "Evaluation of Rutting Potential of Asphalt Mixtures Using Linear Genetic Programming",
- booktitle = "The 11th International Conference on Asphalt Pavements (ISAP 2010)",
- year = "2010",
- volume = "2",
- pages = "1527--1536?",
- address = "Nagoya, Japan",
- publisher_address = "57 Morehouse Lane Red Hook, NY 12571 USA Phone: 845-758-0400 Fax: 845-758-2634 Email: curran@proceedings.com",
- month = "1-6 " # aug,
- organisation = "International Society for Asphalt Pavements (ISAP) 6776 Lake Drive, Suite 215 Lino Lakes, MN 55014",
- publisher = "Curran Associates, Inc. (Sep 2011)",
- keywords = "genetic algorithms, genetic programming, Rutting, Flow number, Linear genetic programming, Regression Analysis, Marshall mix design",
- isbn13 = "978-1-61839-073-8",
-
URL = "
http://www.proceedings.com/12470.html",
-
URL = "https://www.researchgate.net/publication/236619155_Evaluation_of_Rutting_Potential_of_Asphalt_Mixtures_Using_Linear_Genetic_Programming",
- size = "10 pages",
- abstract = "Rutting has been considered as the most serious distresses in flexible pavement for many years. Flow number obtained from uniaxial dynamic creep test is an explanatory index for the evaluation of rutting potential of asphalt mixtures. This is a pioneer study that presents a promising variant of genetic programming, namely linear genetic programming (LGP) to predict the flow number of dense asphalt-aggregate mixtures. Generalized LGP-based models were constructed to relate the flow number of Marshall specimens to the coarse and fine aggregate contents, percentage of air voids, percentage of voids in mineral aggregate, Marshall stability and flow. The comprehensive experimental database used for the development of the models was established upon a series of uniaxial dynamic creep tests conducted in this study. The contributions of the parameters affecting the flow number were determined through a sensitivity analysis. A multiple least squares regression (MLSR) analysis was performed using the same variables and same data sets to benchmark the LGP models. For more verification, a subsequent parametric study was conducted and the trends of the results were confirmed with the results of previous studies. The results indicate that the proposed LGP models are capable of effectively evaluating the flow number of asphalt mixtures. The LGP models are found to be significantly more accurate than the MLSR model.",
-
notes = "Paper ID.
90316
http://www.gbv.de/dms/tib-ub-hannover/653947240.pdf gives pages as Volume II, 211--220?",
