Artificial neural network approach to estimating stiffness behavior of rubberized asphalt concrete containing reclaimed asphalt pavement

Journal of Transportation Engineering

Volumn 135, Issue 8, 2009, Pages 580-589

  Xiao, Feipeng ^a   Amirkhanian, Serji N ^a  

^a AMRL   (United States)

Author keywords

Asphalt pavements; Concrete pavements; Neural networks; Rubber; Sensitivity analysis; Stiffness

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK APPROACH; ASPHALT MIXTURE; COMPLEX BEHAVIOR; DEPENDENT VARIABLES; ENVIRONMENTAL CONDITIONS; FATIGUE LIFE; INDEPENDENT VARIABLES; INPUT VARIABLES; MATERIAL ENGINEERING; PAVEMENT STRUCTURES; PREDICTION MODEL; RECLAIMED ASPHALT PAVEMENTS; RUBBER CONTENT; RUBBERIZED ASPHALT; STIFFNESS VALUES; TESTING TEMPERATURE;

ASPHALT PAVEMENTS; BACKPROPAGATION; CONCRETE CONSTRUCTION; CONCRETE PAVEMENTS; MATHEMATICAL MODELS; MIXTURES; NEURAL NETWORKS; ROADS AND STREETS; RUBBER; SENSITIVITY ANALYSIS; STIFFNESS;

ASPHALT;

ARTIFICIAL NEURAL NETWORK; ASPHALT; CONCRETE STRUCTURE; ESTIMATION METHOD; PAVEMENT; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS; STIFFNESS;

EID: 68049114610     PISSN: 0733947X     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)TE.1943-5436.0000014     Document Type: Article

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