Multigene Genetic Programming for Estimation of Elastic Modulus of Concrete
Author(s) -
Alireza Mohammadi Bayazidi,
GaiGe Wang,
Hamed Bolandi,
Amir H. Alavi,
Amir H. Gandomi
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/474289
Subject(s) - genetic programming , elastic modulus , tangent , tangent modulus , compressive strength , structural engineering , moduli , materials science , mathematics , computer science , engineering , composite material , artificial intelligence , physics , geometry , quantum mechanics
This paper presents a new multigene genetic programming (MGGP) approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behavior by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalized prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools
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