Estimation of flexural capacity of quadrilateral FRP-confined RC columns using combined artificial neural network
Küçük Resim Yok
Tarih
2012
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER SCI LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study presents the application of combined artificial neural networks (CANNs) for the flexural capacity estimation of quadrilateral fiber-reinforced polymer (FRP) confined reinforced concrete (RC) columns. A database on quadrilateral FRP confined RC columns subjected to axial load and moment was obtained from experimental studies in the literature; CANN models were built, trained and tested. Then the flexural capacities of quadrilateral FRP confined RC columns were determined using the developed CANN model. Single and combined ANN was used for the first time in the literature for the estimation of flexural capacities of non-circular fiber-reinforced polymer (FRP) confined reinforced concrete (RC) columns. The accuracies of the proposed ANN and CANN models were more satisfactory as compared to the existing conventional approaches in the literature. Moreover, the proposed CANN models' results had lower prediction error than those of the single ANN model. (C) 2012 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Confined column, Fiber-reinforced polymer, Experiment, Combined artificial neural networks
Kaynak
ENGINEERING STRUCTURES
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
42
