Evaluating the strength of intact rocks through genetic programming

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@Article{Asadi:2010:ASC,

• author = "Mojtaba Asadi and Mehdi Eftekhari and Mohammad Hossein Bagheripour",
• title = "Evaluating the strength of intact rocks through genetic programming",
• journal = "Applied Soft Computing",
• year = "2011",
• volume = "11",
• number = "2",
• pages = "1932--1937",
• month = mar,
• keywords = "genetic algorithms, genetic programming, Information criterion, Intact rock, Failure criteria",
• ISSN = "1568-4946",
• URL = "http://www.sciencedirect.com/science/article/B6W86-50CVPW4-2/2/863c13a5a1c7be6da7b1ea6592b11bd3",
• DOI = "doi:10.1016/j.asoc.2010.06.009",
• size = "13 pages",
• abstract = "Good prediction of the strength of rocks has many theoretical and practical applications. Analysis, design and construction of underground openings and tunnels, open pit mines and rock-based foundations are some examples of applications in which prediction of the strength of rocks is of great importance. The prediction might be done using mathematical expressions called failure criteria. In most cases, failure criteria of jointed rocks contain the value of strength of intact rock, i.e. the rock without joints and cracks. Therefore, the strength of intact rock can be used directly in applications and indirectly to predict the strength of jointed rock masses. On the other part, genetic programming method is one of the most powerful methods in machine learning field and could be used for non-linear regression problems. The derivation of an appropriate equation for evaluating the strength of intact rock is the common objective of many researchers in civil and mining engineering; therefore, mathematical expressions were derived in this paper to predict the strength of the rock using a genetic programming approach. The data of 51 rock types were used and the efficiency of equations obtained was illustrated graphically through figures.",
• notes = "a Sirjan engineering college, Department of Civil Engineering, Iran b Shahid Bahonar University of Kerman, Department of Computer Engineering, Iran c Shahid Bahonar University of Kerman, Department of Civil Engineering, Iran",

}

Genetic Programming entries for Mojtaba Asadi Mehdi Eftekhari Mohammad Hossein Bagheripour

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