The Use of Genetic Programming and Regression Analysis for Modeling the Modulus of Elasticity of NSC and HSC
Küçük Resim Yok
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER HEIDELBERG
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Artificial intelligence has recently drawn the attention of explorers to predict the physical, chemical and mechanical properties of normal-strength concrete (NSC) and high-strength concrete (HSC). This study presents gene expression programming (GEP) and regression analysis (RA) for modeling the modulus of elasticity (E-c) from the compressive strength (f(c)) values of NSC and HSC. In order to create the models, experimental results of NSC and HSC are collected from the published literature. The evaluated results by training, testing and checking of the GEP and RA models are compared with the results obtained from the experimental studies, the formulations presented by some national building codes and the formulations proposed by some authors available in the literature. These comparisons and statistic results show that GEP and RA models are very effective methods for calculating the E-c from f(c) of NSC and HSC.
Açıklama
Anahtar Kelimeler
Compressive strength, Modulus of elasticity, Genetic programming, Regression analysis
Kaynak
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
41
Sayı
10
