An adaptive neuro-fuzzy inference system for predicting unconfined compressive strength and Young's modulus: a study on Main Range granite

D Jahed Armaghani, E Tonnizam Mohamad… - Bulletin of engineering …, 2015 - Springer
Engineering properties of rocks such as unconfined compressive strength (UCS) and
Young's modulus (E) are among the essential parameters for the design of tunnel …

Predicting triaxial compressive strength and Young's modulus of frozen sand using artificial intelligence methods

M Esmaeili-Falak, H Katebi, M Vadiati… - Journal of Cold …, 2019 - ascelibrary.org
Mechanical properties of frozen soils (eg, triaxial compressive strength, σ tc and Young's
modulus, E) are important in tunnel, shaft, or open pit excavation projects. Although …

[HTML][HTML] A deep learning method for the prediction of the index mechanical properties and strength parameters of marlstone

M Azarafza, M Hajialilue Bonab, R Derakhshani - Materials, 2022 - mdpi.com
The index mechanical properties, strength, and stiffness parameters of rock materials (ie,
uniaxial compressive strength, c, ϕ, E, and G) are critical factors in the proper geotechnical …

Develo** novel models using neural networks and fuzzy systems for the prediction of strength of rocks from key geomechanical properties

LK Sharma, V Vishal, TN Singh - Measurement, 2017 - Elsevier
This research study was conducted to predict the unconfined compressive strength (UCS) of
the rocks by applying the adaptive neuro-fuzzy inference system (ANFIS), and the outcomes …

A review: applications of fuzzy theory in rock engineering

F Samimi Namin, MM Rouhani - Indian Geotechnical Journal, 2024 - Springer
One of the sub-disciplines of geo-engineering is rock engineering, which studies the
behavior of rocks against internal and external factors. Fuzzy theory can be used to solve …

Advanced tree-based techniques for predicting unconfined compressive strength of rock material employing non-destructive and petrographic tests

Y Wang, M Hasanipanah, ASA Rashid, BN Le… - Materials, 2023 - mdpi.com
The accurate estimation of rock strength is an essential task in almost all rock-based
projects, such as tunnelling and excavation. Numerous efforts to create indirect techniques …

[HTML][HTML] Prediction of the uniaxial compressive strength of rocks from simple index tests using a random forest predictive model

M Wang, W Wan, Y Zhao - Comptes …, 2020 - comptes-rendus.academie-sciences …
Uniaxial compressive strength (UCS) is an important mechanical parameter for stability
assessments in rock mass engineering. In practice, obtaining the UCS simply, accurately …

Prediction of the uniaxial compressive strength of rocks by soft computing approaches

R Khajevand - Geotechnical and Geological Engineering, 2023 - Springer
The determination of uniaxial compressive strength (UCS) is one of the most important
mechanical properties of rocks. The direct measurement of UCS using laboratory methods is …

Applying improved artificial neural network models to evaluate drilling rate index

H Fattahi, H Bazdar - Tunnelling and Underground Space Technology, 2017 - Elsevier
The drilling rate index (DRI) is the most important input parameter of a commonly used
performance prediction model for drilling and rock excavation. In this paper, the hybrid …

Shear wave velocity estimation from conventional well log data by using a hybrid ant colony–fuzzy inference system: A case study from Cheshmeh–Khosh oilfield

A Nourafkan, A Kadkhodaie-Ilkhchi - Journal of Petroleum Science and …, 2015 - Elsevier
Abstract Characterization of geomechanical parameters of hydrocarbon reservoirs such as
compressional and shear wave velocities is a main component of petrophysical …