The Use of Genetic Programming and Regression Analysis for Modeling the Modulus of Elasticity of NSC and HSC

Küçük Resim Yok

Tarih

2016

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

Künye