Empirical modeling of splitting tensile strength from cylinder compressive strength of concrete by genetic programming

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@Article{Saridemir2011,

• author = "Mustafa Saridemir",
• title = "Empirical modeling of splitting tensile strength from cylinder compressive strength of concrete by genetic programming",
• journal = "Expert Systems with Applications",
• year = "2011",
• volume = "38",
• number = "11",
• pages = "14257--14268",
• ISSN = "0957-4174",
• DOI = "doi:10.1016/j.eswa.2011.04.239",
• URL = "http://www.sciencedirect.com/science/article/B6V03-52SBMC3-12/2/8a0a7f9c46f4df0267c921c80fd0bd56",
• keywords = "genetic algorithms, genetic programming, gene expression programming, Compressive strength, Splitting tensile strength",
• size = "12 pages",
• abstract = "Compressive strength and splitting tensile strength are both mechanical properties of concrete that are used in structural design. This study presents gene expression programming (GEP) as a new tool for the formulations of splitting tensile strength from compressive strength of concrete. For purpose of building the GEP-based formulations, 536 experimental data have been gathered from existing literature. The GEP-based formulations are developed for splitting tensile strength of concrete as a function of age of specimen and cylinder compressive strength. In experimental parts of this study, cylindrical specimens of 150 times 300 mm and 100 times 200 mm in dimensions were used. Training and testing sets of the GEP-based formulations were randomly separated from the complete experimental data. The GEP-based formulations were also validated with additional 173 data of experimental results other than the data used in training and testing sets of the GEP-based formulations. All of the results obtained from the GEP-based formulations were compared with the results obtained from experimental data, the developed regression-based formulation and formulas given by some national building codes. These comparisons showed that the GEP-based formulations appeared to well agree with the experimental data and found to be quite reliable.",

}

Genetic Programming entries for Mustafa Saridemir

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