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Geomechanics and Geoengineering
An International Journal
Volume 17, 2022 - Issue 2
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Research Article

Prediction of the shear strength parameters from easily-available soil properties by means of multivariate regression and artificial neural network methods

Mojtaba Mohammadia Department of Applied Geology, Faculty of Earth Science, Kharazmi University, Tehran, Iran
,
Seyed Mahmoud Fatemi Aghdaa Department of Applied Geology, Faculty of Earth Science, Kharazmi University, Tehran, IranCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-4368-273X
ORCID Icon,
Mehdi Talkhabloua Department of Applied Geology, Faculty of Earth Science, Kharazmi University, Tehran, Iran
&
Akbar Cheshomib Department of Geology, University of Tehran, Tehran, Iran
Pages 442-454 | Received 15 Dec 2019, Accepted 01 Jun 2020, Published online: 25 Jun 2020

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Arunav Chakraborty & Anasuya Goswami. (2022) Mathematical Model for Estimation of Shear Parameters of Alluvial Soils of Kamrup Metro District (Assam, India) from Index Properties. Australian Journal of Civil Engineering 0:0, pages 1-12.
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Articles from other publishers (4)

Ehsan Momeni, Biao He, Yasin Abdi & Danial Jahed Armaghani. (2023) Novel Hybrid XGBoost Model to Forecast Soil Shear Strength Based on Some Soil Index Tests. Computer Modeling in Engineering & Sciences 136:3, pages 2527-2550.
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Mohammad Reza Hatef, Akbar Ghazifard & Mojtaba Kamani. (2023) Assessments of the abrasion resistance of carbonate aggregates using petrological characteristics. Arabian Journal of Geosciences 16:1.
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Tuan Anh Pham, Van Quan Tran & Huong-Lan Thi Vu. (2021) Evolution of Deep Neural Network Architecture Using Particle Swarm Optimization to Improve the Performance in Determining the Friction Angle of Soil. Mathematical Problems in Engineering 2021, pages 1-17.
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Sparsh Sharma, Suhaib Ahmed, Mohd Naseem, Waleed S. Alnumay, Saurabh Singh & Gi Hwan Cho. (2021) A Survey on Applications of Artificial Intelligence for Pre-Parametric Project Cost and Soil Shear-Strength Estimation in Construction and Geotechnical Engineering. Sensors 21:2, pages 463.
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