Prediction of compressive and tensile strength of Gaziantep basalts via neural networks and gene expression programming

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@Article{journals/nca/CanakciBG09,

• title = "Prediction of compressive and tensile strength of Gaziantep basalts via neural networks and gene expression programming",
• author = "Hanifi Canakci and Adil Baykasoglu and Hamza Gullu",
• journal = "Neural Computing and Applications",
• year = "2009",
• number = "8",
• volume = "18",
• pages = "1031--1041",
• keywords = "genetic algorithms, genetic programming, gene expression programming, Artificial neural networks, Basalt, Tensile and compressive strength",
• DOI = "doi:10.1007/s00521-008-0208-0",
• abstract = "In this paper, two soft computing approaches, which are known as artificial neural networks and Gene Expression Programming (GEP) are used in strength prediction of basalts which are collected from Gaziantep region in Turkey. The collected basalts samples are tested in the geotechnical engineering laboratory of the University of Gaziantep. The parameters, ultrasound pulse velocity, water absorption, dry density, saturated density, and bulk density which are experimentally determined based on the procedures given in ISRM (Rock characterisation testing and monitoring. Pergamon Press, Oxford, 1981) are used to predict uniaxial compressive strength and tensile strength of Gaziantep basalts. It is found out that neural networks are quite effective in comparison to GEP and classical regression analyses in predicting the strength of the basalts. The results obtained are also useful in characterizing the Gaziantep basalts for practical applications.",
• notes = "Department of Civil Engineering, University of Gaziantep, Gaziantep, Turkey (2) Department of Industrial Engineering, Faculty of Engineering, University of Gaziantep, 27310 Gaziantep, Turkey",
• bibdate = "2009-12-11",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/nca/nca18.html#CanakciBG09",

}

Genetic Programming entries for Hanifi Canakci Adil Baykasoglu Hamza Gullu

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