• DocumentCode
    3642094
  • Title

    Determining amount of bituminous effects on asphalt concrete strength with artificial intelligence and statistical analysis methods

  • Author

    Sercan Serin;Nihat Morova;Serdal Terzi;Şebnem Sargin

  • Author_Institution
    Department of Contraction, Education, Technical Education, Faculty, Duzce University, Duzce, 81620 Turkey
  • fYear
    2011
  • fDate
    6/1/2011 12:00:00 AM
  • Firstpage
    329
  • Lastpage
    334
  • Abstract
    In this study, an experimental study has been conducted to determine compressive strength of asphalt concrete. The scope of study by preparing 45 Marshall samples Marshall stability experiment was conducted and compressive strength of asphalt concrete was determined. Compressive strength of asphalt concrete as depending on bituminous amount prediction models were developed by using obtained experiment results. Compressive strength of asphalt concrete values as depending on bituminous amount have been estimated on prediction models developed with regression analyses and Artificial Neural Network (ANN) Methods. Results obtained from models were compared with experiment results. Prediction performances of developed models were evaluated as compared. As a result it was determined that possible to estimate the compressive strength of asphalt concrete as depending on bituminous amount with developed ANN model and that ANN model was more successful than regression model for estimating the compressive strength of asphalt concrete.
  • Keywords
    "Asphalt","Artificial neural networks","Concrete","Neurons","Data models","Aggregates"
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on
  • Print_ISBN
    978-1-61284-919-5
  • Type

    conf

  • DOI
    10.1109/INISTA.2011.5946139
  • Filename
    5946139