Prediction of compressive strength of heavyweight concrete by ANN and FL models
Yükleniyor...
Dosyalar
Tarih
2010
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The compressive strength of heavyweight concrete which is produced using baryte aggregates has been predicted by artificial neural network (ANN) and fuzzy logic (FL) models. For these models 45 experimental results were used and trained. Cement rate, water rate, periods (7-28-90 days) and baryte (BaSO(4)) rate (%) were used as inputs and compressive strength (MPa) was used as output while developing both ANN and FL models. In the models, training and testing results have shown that ANN and FL systems have strong potential for predicting compressive strength of concretes containing baryte (BaSO(4)).
Açıklama
Akkurt, Iskender/0000-0002-5247-7850; Kilincarslan, Semsettin/0000-0001-8253-9357
WOS: 000277940600001
WOS: 000277940600001
Anahtar Kelimeler
Heavyweight concrete, Baryte, Compressive strength, Artificial neural networks, Fuzzy logic, Computer simulation
Kaynak
Neural Computing & Applications
WoS Q Değeri
Q4
Scopus Q Değeri
Cilt
19
Sayı
4
