373
Views
20
CrossRef citations to date
0
Altmetric
Papers

Developing a hybrid artificial neural network-genetic algorithm model to predict resilient modulus of polypropylene/polyester fiber-reinforced asphalt concrete

, &
Pages 1239-1250 | Received 10 Jul 2014, Accepted 05 Nov 2014, Published online: 10 Dec 2014

References

  • Airey, G. D. (2004). Fundamental binder and practical mixture evaluation of polymer modified bituminous materials. International Journal of Pavement Engineering, 5, 137–151.10.1080/10298430412331314146
  • Alibi, H., Fayala, F., Bhouri, N., Jemni, A., & Zeng, X. (2013). An optimal artificial neural network system for designing knit stretch fabrics. The Journal of The Textile Institute, 104, 766–783.10.1080/00405000.2012.756134
  • Almetwally, A. A., Idrees, H. M. F., & Hebeish, A. A. (2014). Predicting the tensile properties of cotton/spandex core-spun yarns using artificial neural network and linear regression models. The Journal of The Textile Institute, 105, 1221–1229.10.1080/00405000.2014.882043
  • Çelik, H. İ., Dülger, L. C., & Topalbekiroğlu, M. (2013). Development of a machine vision system: Real-time fabric defect detection and classification with neural networks. The Journal of The Textile Institute, 105, 575–585.
  • Curteanu, S., & Leon, F. (2008). Optimization strategy based on genetic algorithms and neural networks applied to a polymerization process. International Journal of Quantum Chemistry, 108, 617–630.
  • Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Boston, MA: Addison-Wesley.
  • Huang, H., & White, T. D. (1996). Dynamic properties of fiber-modified overlay mixture. Transportation Research Record, 1545, 98–104.10.3141/1545-13
  • Jahromi, S. G., & Khodaii, A. (2008). carbon fiber reinforced asphalt concrete. The Arabian Journal for Science and Engineering, 33, 355–364.
  • Kim, Y. R. (2009). Modeling of asphalt concrete. New York, NY: McGraw-Hill Professional.
  • Lee, S. J., Rust, J. P., Hamouda, H., Kim, Y. R., & Borden, R. H. (2005). Fatigue cracking resistance of fiber-reinforced asphalt concrete. Textile Research Journal, 75, 123–128.10.1177/004051750507500206
  • Liu, Q., Schlangen, E., van de Ven, M., & García, Á. (2010). Healing of porous asphalt concrete via induction heating. Road Materials and Pavement Design, 11, 527–542.10.1080/14680629.2010.9690345
  • MathWorks-Inc. (2007). Genetic algorithm and direct search toolbox user’s guide. Natick, MA: CRC Press.
  • Minapoor, S., Ajeli, S., Hasani, H., & Shanbeh, M. (2012). Investigation into the curling behavior of single jersey weft-knitted fabrics and its prediction using neural network model. The Journal of The Textile Institute, 104, 550–561.
  • Moghadas Nejad, F., Vadood, M., & Baeetabar, S. (2014). Investigating the mechanical properties of carbon fibre-reinforced asphalt concrete. Road Materials and Pavement Design, 15, 465–475.10.1080/14680629.2013.876442
  • Naghashzargar, E., Semnani, D., Karbasi, S., & Nekoee, H. (2013). Application of intelligent neural network method for prediction of mechanical behavior of wire-rope scaffold in tissue engineering. The Journal of The Textile Institute, 105, 264–274.
  • Najdi, A., Chao, Z., & Ying, G. (2005). Experiments of fracture behavior of glass fiber reinforced asphalt concrete. Journal of Chang’an University, 25, 28–32.
  • Semnani, D., & Vadood, M. (2010). Improvement of intelligent methods for evaluating the apparent quality of knitted fabrics. Engineering Applications of Artificial Intelligence, 23, 217–221.10.1016/j.engappai.2009.08.003
  • Serfass, J., & Samanos, J. (1996). Fiber-modified asphalt concrete characteristics, applications and behavior. Journal of The Association of Asphalt Paving Technologists, 65, 193–230.
  • Shabaridharan, & Das, A. (2013a). Statistical and ANN analysis of thermal and evaporative resistances of multilayered fabric ensembles. The Journal of The Textile Institute, 104, 950–964.10.1080/00405000.2013.766392
  • Shabaridharan, K., & Das, A. (2013b). Modeling of thermal properties of multilayered fabrics by ANN consisting of polypropylene needle-punched nonwovens. The Journal of The Textile Institute, 105, 109–118.
  • Shahrabi, J., Hadavandi, E., & Soltani, P. (2013). Developing an intelligent fiber migration simulator in spun yarns using a genetic fuzzy system. Fibers and Polymers, 14, 844–853.10.1007/s12221-013-0844-6
  • Tapkın, S. (2008). The effect of polypropylene fibers on asphalt performance. Building and Environment, 43, 1065–1071.10.1016/j.buildenv.2007.02.011
  • Uysal, O., & Bulkan, S. (2008). Comparison of genetic algorithm and particle swarm optimization for bicriteria permutation flowshop scheduling problem. International Journal of Computational Intelligence Research, 4, 159–175.
  • Vadood, M., & Semnani, D. (2011). Optimization of fiber distribution in spunbond non-woven structure. Fibers and Polymers, 12, 821–829.10.1007/s12221-011-0821-x
  • Vadood, M., Semnani, D., & Morshed, M. (2011). Optimization of acrylic dry spinning production line by using artificial neural network and genetic algorithm. Journal of Applied Polymer Science, 120, 735–744.10.1002/app.v120.2
  • Wu, S., Ye, Q., & Li, N. (2008). Investigation of rheological and fatigue properties of asphalt mixtures containing polyester fibers. Construction and Building Materials, 22, 2111–2115.10.1016/j.conbuildmat.2007.07.018

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.