Machine learning technology in biodiesel research: A review

M Aghbashlo, W Peng, M Tabatabaei… - Progress in Energy and …, 2021 - Elsevier
Biodiesel has the potential to significantly contribute to making transportation fuels more
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …

Evolving support vector regression using Grey Wolf optimization; forecasting the geomechanical properties of rock

C Xu, M Nait Amar, MA Ghriga, H Ouaer… - Engineering with …, 2022 - Springer
The geomechanical properties of rock, including shear strength (SS) and uniaxial
compressive strength (UCS), are very important parameters in designing rock structures. To …

Machine learning approach to model rock strength: prediction and variable selection with aid of log data

MI Miah, S Ahmed, S Zendehboudi, S Butt - Rock Mechanics and Rock …, 2020 - Springer
Comprehensive knowledge and analysis of in situ rock strength and geo-mechanical
characteristics of rocks are crucial in hydrocarbon and mineral exploration stage to …

Predictive models and feature ranking in reservoir geomechanics: A critical review and research guidelines

MI Miah - Journal of Natural Gas Science and Engineering, 2020 - Elsevier
Comprehensive investigation and accurate models of geo-mechanical properties are crucial
to maintain wellbore stability and optimize the hydraulic fracturing process. This review …

The effect of grain size, porosity and mineralogy on the compressive strength of tight sandstones: A case study from the eastern Ordos Basin, China

Y Qi, Y Ju, K Yu, S Meng, P Qiao - Journal of Petroleum Science and …, 2022 - Elsevier
To better understand how textural properties and mineralogy control compressive strength,
this work performed the grain size analysis, porosity measurement, X-ray diffraction …

Application of soft computing methods in predicting uniaxial compressive strength of the volcanic rocks with different weathering degree

N Ceryan, P Samui - Arabian Journal of Geosciences, 2020 - Springer
Uniaxial compressive strength (UCS) of rock material is very important parameter for rock
engineering applications such as rock mass classification, numerical modelling bearing …

Predicting peak shear strength of rock fractures using tree-based models and convolutional neural network

J Chen, Z Zhao, J Zhang - Computers and Geotechnics, 2024 - Elsevier
It is of significance to estimate peak shear strength (PSS) of rock fractures in engineering
practice, but the existing PSS criteria may not fully represent the 3D characteristics of …

Prediction of uniaxial compressive strength of rock via genetic algorithm—selective ensemble learning

H Zhang, S Wu, Z Zhang - Natural Resources Research, 2022 - Springer
Reasonable and effective determination of uniaxial compressive strength (UCS) is critical for
rock mass engineering stability research, design, and construction. To estimate the UCS of …

Machine learning predictive models to estimate the UCS and tensile strength of rocks in Bakken Field

A Chemmakh - SPE Annual Technical Conference and Exhibition?, 2021 - onepetro.org
Abstract Uniaxial Compressive Strength (UCS) and Tensile Strength (TS) are among the
essential rock parameters required and determined for rock mechanical studies in …

Estimating DEM microparameters for uniaxial compression simulation with genetic programming

M De Simone, LMS Souza, D Roehl - International Journal of Rock …, 2019 - Elsevier
Among the steps in modeling with the Discrete Element Method (DEM), one of the most
important is parameter calibration. The commonly used trial-and-error approach brings …