Adaptive neuro-fuzzy inference approach for prediction the stiffness modulus on asphalt concrete
Yükleniyor...
Dosyalar
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Sci Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, stiffness modulus parameters of asphalt concrete were determined experimentally for different temperature and exposure times. The stiffness modules were calculated according to Nijboer stiffness module. Basic physical properties and the quantity of bitumen of asphalt core samples were designated for determining the stiffness modules. The samples were exposed to 17 degrees C (reference temperature), 30, 40 and 50 degrees C temperatures for 1.5, 3, 4.5 and 6 h respectively and then Marhall Stability tests were done for each samples. By using the test results a prediction model with Sugeno type based on the adaptive neuron-fuzzy inference system (ANFIS) was alternatively developed to predict the stiffness modules of asphalt core samples. As a result, it was seen that the developed prediction model could be used as a prediction model for unperformed situations which are not suitable for experiments. (C) 2011 Elsevier Ltd. All rights reserved.
Açıklama
Emiroglu, Mehmet/0000-0002-0214-4986
WOS: 000299803100011
WOS: 000299803100011
Anahtar Kelimeler
Asphalt concrete, Stiffness modulus, Prediction model, Sugeno fuzzy inference, Temperature effect, Exposure times
Kaynak
Advances In Engineering Software
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
45
Sayı
1
