Proposing a new model to approximate the elasticity modulus of granite rock samples based on laboratory tests results-Reference-Cited by-同舟云学术

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Proposing a new model to approximate the elasticity modulus of granite rock samples based on laboratory tests results

Published:2017-12-08 Issue:3 Volume:78 Page:1527-1536
ISSN:1435-9529
Container-title:Bulletin of Engineering Geology and the Environment
language:en
Short-container-title:Bull Eng Geol Environ

Author:

Behzadafshar Katayoun,Sarafraz Mehdi Esfandi,Hasanipanah Mahdi,Mojtahedi S. Farid F.,Tahir M. M.

Publisher

Springer Science and Business Media LLC

Subject

Geology,Geotechnical Engineering and Engineering Geology

Link

http://link.springer.com/content/pdf/10.1007/s10064-017-1210-5.pdf

Reference73 articles.

1. Armaghani DJ, Faradonbeh RS, Rezaei H et al (2016a) Settlement prediction of the rock-socketed piles through a new technique based on gene expression programming. Neural Comput Appl. https://doi.org/10.1007/s00521-016-2618-8

2. Ahmad M, Ansari MK, Sharma LK, Singh R, Singh TN (2017) Correlation between strength and durability indices of rocks-soft computing approach. Proc Eng 191:458–466

3. Armaghani DJ, Mahdiyar A, Hasanipanah M et al (2016b) Risk assessment and prediction of flyrock distance by combined multiple regression analysis and Monte Carlo simulation of quarry blasting. Rock Mech Rock Eng 49:1–11. https://doi.org/10.1007/s00603-016-1015-z

4. Armaghani DJ, Mohamad ET, Momeni E et al (2016c) Prediction of the strength and elasticity modulus of granite through an expert artificial neural network. Arab J Geosci 9:48

5. Baykasoğlu A, Güllü H, Çanakçı H, Özbakır L (2008) Prediction of compressive and tensile strength of limestone via genetic programming. Expert Syst Appl 35:111–123

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