Modelling Marshall Stability of fiber reinforced asphalt mixtures with ANFIS

MOROVA N., ERİŞKİN E., TERZİ S., KARAHANÇER Ş., Serin S., SALTAN M., ...More

2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2017, Gdynia, Poland, 3 - 05 July 2017, pp.174-179, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/inista.2017.8001152
  • City: Gdynia
  • Country: Poland
  • Page Numbers: pp.174-179
  • Keywords: Adaptive Neural Fuzzy Inference System (ANFIS), Asphalt Concrete, Basalt Fiber, Marshall Stability
  • Isparta University of Applied Sciences Affiliated: No

Abstract

In this study, an Adaptive Neural Fuzzy Inference System (ANFIS) model for predicting the Marshall Stability (MS) of basalt fiber reinforced asphalt concrete mixtures and various mix proportions has been developed. Experimental details were used to construct the model. The amounts of bitumen (%), Fiber (Basalt) Ratio (%) were used as input variables and Marshall Stability (kg) values were used as output variables. Statistical equations were used to evaluate the Developed ANFIS model. Results showed that developed ANFIS model has strong potential to predict Marshall Stability of asphalt concrete using related inputs in a short time. Also, the Marshall Stability of Fiber-Reinforced asphalt concrete and various mix proportions can be found without performing any experiments.