-بهبهانی، ح.، ایازی، م. ج.، و شجاعی، م. ح.، (1395)، "ارزیابی آزمایشگاهی حساسیت رطوبتی و پتانسیل شیار شدگی مخلوطهای آسفالتی نیمه گرم"، مهندسی حمل و نقل، سال هفتم، بهار، ص.418-405.
- McCulloch, D. and K, Vukadinovic, (2012), "Trafiic Control and Transport Planning: A Fuzzy Sets and Neural Networks Approach",
Vol. 13, Springer Science & Business Media.
-M. Lazarevska, M. Knezevic, M. Cvetkovska, A.G. Trombeva, (2014), “Application of artificial neural networks in civil engineering”, Tech. Gazette 21 (6),
pp. 1353-1359.
-I. Flood, (1990), “Simulating the construction process using neural networks, in: Proceedings of the 7th ISARC – International Association for Automation and Rrobotics in Construction/Bristol”,
pp. 374-382.
-D.S. Jeng, D.H. Cha, m. Blumenstein, (2003), “Application of neural networks in civil engineering problems, in: Proceeding of the International Conference on Advance in the Internet, Processing, Systems and Interdisciplinary Research”.
-E. Ozgan, (2011), “Artificial neural network based modelling of the Marshall Stability of asphalt concrete, Expert Systems with Applications”, 38(2011), pp.6025-6030.
-
Gh.Shafabakhsh, O. Jafari Ani, M. Talebsafa, (2015), “artificial neural network modeling (ANN) for predicring rutting performance of nano-modified hot-mix asphalt mixtures containing Steel slag aggregates,
Construction and Building Materials”, pp.136-143.
-F. Xiao, S. Amirkhanian, C. Hsein, (2009), “prediction of fatigue life of rubberized asphalt concrete mixtures containing reclaimed asphalt pavement using artificial neural network, J. Master. Civ. Eng. 21 (6), pp.253-261.
- F. Xiao, S., (2015), “Amirkhanian, artificial neural network approach to estimating stiffness behaviour of rubberized asphalt concrete mixtures containing reclaimed asphalt pavement,, J. Transp. Eng. 59 (3),
pp. 249-264.
-M. Firouzinia, Gh. Shafabakhsh, (2018), “Investigation of the effect of nano-silica on thermal sensitivity of HMA using artificial neural network, Construction and Building Materials 170, pp.527–53.
- Serkan Tapkın, Abdulkadir Çevik, Ün Usar, (2010), “Prediction of Marshall test results for polypropylene modified dense bituminous mixtures using neural networks, Expert Systems with Applications 37,
pp. 4660–4670
- Halil Ceylan , Alper Guclu , Erol Tutumluer & Marshall R. Thompson, (2005), “Back calculation of full-depth asphalt pavement layer moduli considering nonlinear
stress-dependent subgrade behaviour”, International Journal of Pavement Engineering, 6:3, pp.171-182.
-Eldin, N. N., & Senouci, A. B., (1995), “A pavement condition rating model using back propagation neural network. Microcomputers in Civil Engineering, 10(6), pp.433-441.
-Ivica Androjic, Zlata Dolacˇek-Alduk, (2018), “Artificial neural network model for forecasting energy consumption in hot mix asphalt (HMA) production”, Construction and Building Materials 170, pp.424–43.
-Golzar, K., A. Jalali.arami, and M., (2012), “Nematollahi, Statistical investigation on physical-mechanical properties of base and polymer modified bitumen using Artificial Neural Network’, Construction and Building Materials, 37, pp. 822-831.
- Shi, X., et al., (2011), “Exploring the interactions of chloride deicer solutions with nanomodified and micromodified asphalt mixtures using artificial neural networks”, Journal of Materials in Civil Engineering, 24(7): pp. 805-815.
)