Performance Evaluation of Asphalt Pavement Based on BP Neural Network
Arifovic J, Gençay R. Using genetic algorithms to select architecture of a feedforward artificial neural network. Physica A Statistical Mechanics & Its Applications 2001; 289(3): 574-94.
Blanco A, Delgado M, Pegalajar MC. A real-coded genetic algorithm for training recurrent neural networks. Neural Networks 2001; 14(1): 93-105.
Dubovsky EV, Russell CD, Bischof-Delaloye A, Bubeck B, Chaiwatanarat T, Hilson AJ. Report of the radionuclides in nephrourology committee for evaluation of transplanted kidney (review of techniques). Seminars in Nuclear Medicine 1999; 29(2): 175-88.
Duffuaa SO, Wahhab HIA, Ramadhan RH. The use of an analytical hierarchy process in pavement maintenance priority ranking. Journal of Quality in Maintenance Engineering 1999; 5(1): 25-39.
Evdorides HT, Snaith MS. A knowledge-based analysis process for road pavement condition assessment. Transport 2015; 117(3): 202-10.
Fwa TF, Chan WT, Hoque KZ. Analysis of pavement management activities programming by genetic algorithms. Transportation Research Record Journal of the Transportation Research Board 1998; 1643(1): 1-6.
Giustozzi F, Crispino M, Flintsch G. Multi-attribute life cycle assessment of preventive maintenance treatments on road pavements for achieving environmental sustainability. International Journal of Life Cycle Assessment 2012; 17(4): 409-19.
Guillaumot VM, Durango-Cohen PL, Madanat SM. Adaptive optimization of infrastructure maintenance and inspection decisions under performance model uncertainty. Journal of Infrastructure Systems 2004; 9(4): 133-39.
Gupta JND, Sexton RS. Comparing backpropagation with a genetic algorithm for neural network training. Omega 1999; 27(6): 679-84.
Lin HB, Li Q, Ding R. Simulation study on stress intensity factors of surface crack of hollow axle, Mathematical Modelling of Engineering Problems 2016; 3(4): 179-183.
Lou Z, Gunaratne M, Lu JJ, Dietrich B. Application of neural network model to forecast short-term pavement crack condition: florida case study. Journal of Infrastructure Systems 2001; 7(4): 166-71.
Shekharan AR. Effect of noisy data on pavement performance prediction by artificial neural networks. Transportation Research Record Journal of the Transportation Research Board 1998; 1643(1): 7-13.
Wong WG, He G. Gray evaluation method of concrete pavement comprehensive condition. Journal of Transportation Engineering 1999; 125(6): 547-51.
Wong WG, Luk ST, Guiping HE. A multiple-point excitation prediction model of pavement management. Civil Engineering Systems 2002; 19(3): 209-22.
Yang J, Gunaratne M, Lu JJ, Dietrich B. Use of recurrent markov chains for modeling the crack performance of flexible pavements. Journal of Transportation Engineering 2005; 131(11): 861-72.
Yu B, Lu Q. Life cycle assessment of pavement: methodology and case study. Transportation Research Part D 2012; 17(5): 380-88.