PREDICTION OF THE PERFORMANCE OF BITUMINOUS MIXES USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMS

Jonata Jefferson Andrade, Leonardo Goliatt Da Fonseca, Michèle Farage, Geraldo Luciano de Oliveira Marques
2020 Revista Mundi Engenharia Tecnologia e Gestão (ISSN 2525-4782)  
Accurately forecast performance and durability is a critical issue for improving the design of new and existing pavements. The poor pavement performance increases traffic congestion, compromises safety, and raises maintenance costs due to frequent repairs. The resilient modulus is one of the most critical unbound material property inputs in several current pavement design procedures. Recent studies have addressed the problem of resilient modulus prediction using different methods, including
more » ... hods, including computational intelligence approaches. In this paper, a hybrid intelligent system called ANFIS (Adaptive Neuro-Fuzzy Inference System) is used for predicting the resilient modulus from an experimental database of 270 distinct compositions. ANFIS achieved superior performance when estimating the resilient modulus of bituminous mixes, which can potentially save laboratory resources.
doi:10.21575/25254782rmetg2020vol5n61367 fatcat:gyclhke7hncwbfm3qjojensgpm