A new approach for modeling of flow number of asphalt mixtures

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• 作者：Amir H. Alavi ; ^{alavi@msu.edu} ; ^{ah_alavi@hotmail.com} ; Hassene Hasni ; Imen Zaabar ; Nizar Lajnef
• 关键词：Asphalt mixture ; Flow number ; Multi-gene genetic programming ; Marshall mix design
• 刊名：Archives of Civil and Mechanical Engineering
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：17
• 期：2
• 页码：326-335
• 全文大小：2117 K
• 卷排序：17

文摘

Flow number of asphalt-aggregate mixtures is an explanatory parameter for the analysis of rutting potential of asphalt mixtures. In this study, a new model is proposed for the determination of flow number using a robust computational intelligence technique, called multi-gene genetic programming (MGGP). MGGP integrates genetic programming and classical regression to formulate the flow number of Marshall Specimens. A reliable experimental database is used to develop the proposed model. Different analyses are performed for the performance evaluation of the model. On the basis of a comparison study, the MGGP model performs superior to the models found in the literature.