Neuro-fuzzy and artificial neural networks modeling of uniform temperature effects of symmetric parabolic haunched beams
Küçük Resim Yok
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
TECHNO-PRESS
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
When the temperature of a structure varies, there is a tendency to produce changes in the shape of the structure. The resulting actions may be of considerable importance in the analysis of the structures having non-prismatic members. The computation of design forces for the non-prismatic beams having symmetrical parabolic haunches (NBSPH) is fairly difficult because of the parabolic change of the cross section. Due to their non-prismatic geometrical configuration, their assessment, particularly the computation of fixed-end horizontal forces and fixed-end moments becomes a complex problem. In this study, the efficiency of the Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) in predicting the design forces and the design moments of the NBSPH due to temperature changes was investigated. Previously obtained finite element analyses results in the literature were used to train and test the ANN and ANFIS models. The performances of the different models were evaluated by comparing the corresponding values of mean squared errors (MSE) and decisive coefficients (R-2). In addition to this, the comparison of ANN and ANFIS with traditional methods was made by setting up Linear-regression (LR) model.
Açıklama
Anahtar Kelimeler
non-prismatic member, finite element analysis, parabolic haunch, artificial neural networks, adaptive neuro fuzzy inference systems
Kaynak
STRUCTURAL ENGINEERING AND MECHANICS
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
56
Sayı
5
