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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