An ensemble tree-based machine learning model for predicting the uniaxial compressive strength of travertine rocks

Author:

Barzegar Rahim,Sattarpour Masoud,Deo Ravinesh,Fijani Elham,Adamowski Jan

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference67 articles.

1. Dehghan S, Sattari GH, Chehreh-Chelgani S, Aliabadi MA (2010) Prediction of uniaxial compressive strength and modulus of elasticity for Travertine samples using regression and artificial neural networks. Min Sci Technol 20:41–46

2. Ozbek A, Unsal M, Dikec A (2013) Estimating uniaxial compressive strength of rocks using genetic expression programming. Rock Mech Geotech Eng 5(4):325–329

3. Briševac Z, Hrzenjak P, Buljan R (2016) Models for estimating uniaxial compressive strength and elastic modulus. Gradevinar 68(1):19–28

4. Karakus M, Tutmez B (2006) Fuzzy and multiple regression modeling for evaluation of intact rock strength based on point load, Schmidt hammer and sonic velocity. Rock Mech Rock Eng 39(1):45–57

5. Yilmaz I, Yuksek AG (2008) An example of artificial neural network (ANN) application for indirect estimation of rock parameters. Rock Mech Rock Eng 41:781–795

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