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)-Reference-Cited by-同舟云学术

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)

Published:2021-06-06 Issue:1 Volume:47 Page:629-639
ISSN:2193-567X
Container-title:Arabian Journal for Science and Engineering
language:en
Short-container-title:Arab J Sci Eng

Author:

Özdemir Engin^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

https://link.springer.com/content/pdf/10.1007/s13369-021-05761-x.pdf

Reference76 articles.

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3. Deere, D.U.; Miller, R.P.: Engineering classification and index properties of intact rock. Tech rep no. AFWL-TR 65-116. Univ Illinois: 300 (1966)

4. Singh, R.N.; Hassani, F.P.; Elkington, P.A.S.: The application of strength and deformation index testing to the stability assessment of coal measures excavations. In: Proc 24th US Symp rock Mech, Texas, AEG. Balkema, Rotterdam, 599–609 (1983)

5. Sheorey, P.R.; Barat, D.; Das, M.N.; Mukherjee, K.P.; Singh, B.: Schmidt hammer rebound data for estimation of large scale in situ coal strength. Int. J. Rock Mech. Min. Sci. 21, 39–42 (1984)

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