Modeling deformation modulus of a stratified sedimentary rock mass using neural network, fuzzy inference and genetic programming
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- @Article{Alemdag:2016:EG,
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author = "S. Alemdag and Z. Gurocak and A. Cevik and
A. F. Cabalar and C. Gokceoglu",
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title = "Modeling deformation modulus of a stratified
sedimentary rock mass using neural network, fuzzy
inference and genetic programming",
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journal = "Engineering Geology",
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volume = "203",
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pages = "70--82",
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year = "2016",
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note = "Special Issue on Probabilistic and Soft Computing
Methods for Engineering Geology",
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ISSN = "0013-7952",
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DOI = "doi:10.1016/j.enggeo.2015.12.002",
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URL = "http://www.sciencedirect.com/science/article/pii/S0013795215300971",
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abstract = "This paper investigates a series of experimental
results and numerical simulations employed to estimate
the deformation modulus of a stratified rock mass. The
deformation modulus of rock mass has a significant
importance for some applications in engineering geology
and geotechnical projects including foundation, slope,
and tunnel designs. Deformation modulus of a rock mass
can be determined using large scale in-situ tests. This
large scale sophisticated in-situ testing equipments
are sometimes difficult to install, plus time consuming
to be employed in the field. Therefore, this study aims
to estimate indirectly the deformation modulus values
via empirical methods such as the neural network, neuro
fuzzy and genetic programming approaches. A series of
analyses have been developed for correlating various
relationships between the deformation modulus of rock
mass, rock mass rating, rock quality designation,
uniaxial compressive strength, and elasticity modulus
of intact rock parameters. The performance capacities
of proposed models are assessed and found as quite
satisfactory. At the completion of a comparative study
on the accuracy of models, in the results, it is seen
that overall genetic programming models yielded more
precise results than neural network and neuro fuzzy
models.",
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keywords = "genetic algorithms, genetic programming, Deformation
modulus, Rock mass, Neural network, Neuro fuzzy",
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notes = "Department of Geological Engineering, Gumushane
University, Gumushane 29000, Turkey",
- }
Genetic Programming entries for
Selcuk Alemdag
Z Gurocak
Abdulkadir Cevik
Ali Firat Cabalar
Candan Gokceoglu
Citations