A New Predictive Model for Uniaxial Compressive Strength of Rock Using Machine Learning Method: Artificial Intelligence-Based Age-Layered Population Structure Genetic Programming (ALPS-GP)

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@Article{ozdemir:2022:AJSE,

• author = "Engin Ozdemir",
• title = "A New Predictive Model for Uniaxial Compressive Strength of Rock Using Machine Learning Method: Artificial {Intelligence-Based} {Age-Layered} Population Structure Genetic Programming {(ALPS-GP)}",
• journal = "Arabian Journal for Science and Engineering",
• year = "2022",
• volume = "47",
• number = "1",
• pages = "629--639",
• keywords = "genetic algorithms, genetic programming, ALPS-GP, Uniaxial compressive strength (UCS), ANN, XAI, Stone, Rock, porosity, Schmidt hammer hardness, P-wave velocity, Turkey",
• ISSN = "2193-567X",
• URL = "http://link.springer.com/article/10.1007/s13369-021-05761-x",
• DOI = "10.1007/s13369-021-05761-x",
• abstract = "... The most important advantage of the ALPS-GP model is providing an equation for Uniaxial compressive strength estimation ... it can be used on similar rock types (limestone, dolomite and onyx)",
• notes = "Department of Mining Engineering, Inonu University, Malatya, Turkey",

}

Genetic Programming entries for Engin Ozdemir

Citations