Özgan, Ercan2020-04-302020-04-3020110957-4174https://doi.org/10.1016/j.eswa.2010.11.018https://hdl.handle.net/20.500.12684/2794WOS: 000287419900154In this study, the Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modeled by using artificial neural network. In order to investigate the MS based on physical properties, exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6 h and temperatures of 30 degrees C, 40 degrees C and 50 degrees C were selected. The results showed that at the environment temperature of 17 degrees C the stability of the asphalt core samples decreased by 40.16% at 30 degrees C after 1.5 h and 62.39% after 6 h. At 40 degrees C, the decrease was 74.31% after 1.5 and 78.10% after 6 h. At 50 degrees C the stability of the asphalt decreased by 83.22% after 1.5 h, and 88.66% after 6 h. Experiment results and ANN model exhibited good correlation for this reason the ANN method could be used to model the MS. (C) 2010 Elsevier Ltd. All rights reserved.en10.1016/j.eswa.2010.11.018info:eu-repo/semantics/closedAccessArtificial neural networkAsphalt concreteMarshall StabilityTemperatureArticle38560256030WOS:000287419900154Q1Q1