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Relationship between fatigue life of asphalt concrete and polypropylene/polyester fibers using artificial neural network and genetic algorithm

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Abstract

While various kinds of fibers are used to improve the hot mix asphalt (HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network (ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm (GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy (correlation coefficient of 0.96).

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Authors and Affiliations

  1. Textile Engineering Department, Amirkabir University of Technology, Tehran, Iran

    Morteza Vadood & Majid Safar Johari

  2. Civil and Environmental Engineering Department, Amirkabir University of Technology, Tehran, Iran

    Ali Reza Rahai

Authors
  1. Morteza Vadood
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  2. Majid Safar Johari
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  3. Ali Reza Rahai
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Correspondence to Majid Safar Johari.

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Vadood, M., Johari, M.S. & Rahai, A.R. Relationship between fatigue life of asphalt concrete and polypropylene/polyester fibers using artificial neural network and genetic algorithm. J. Cent. South Univ. 22, 1937–1946 (2015). https://doi.org/10.1007/s11771-015-2713-5

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  • DOI: https://doi.org/10.1007/s11771-015-2713-5

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