Application of Six Metaheuristic Optimization Algorithms and Random Forest in the uniaxial compressive strength of rock prediction

J Li, C Li, S Zhang - Applied Soft Computing, 2022 - Elsevier
The uniaxial compressive strength (UCS) is one of the most important parameters for
judging the mechanical behaviour of rock mass in rock engineering design and excavation …

Prediction of UCS of fine-grained soil based on machine learning part 2: comparison between hybrid relevance vector machine and Gaussian process regression

J Khatti, KS Grover - Multiscale and Multidisciplinary Modeling …, 2024 - Springer
The present research employs the models based on the relevance vector machine (RVM)
approach to predict the unconfined compressive strength (UCS) of the cohesive virgin (fine …

A kernel extreme learning machine-grey wolf optimizer (KELM-GWO) model to predict uniaxial compressive strength of rock

C Li, J Zhou, D Dias, Y Gui - Applied Sciences, 2022 - mdpi.com
Uniaxial compressive strength (UCS) is one of the most important parameters to
characterize the rock mass in geotechnical engineering design and construction. In this …

Hybrid soft computing models for predicting unconfined compressive strength of lime stabilized soil using strength property of virgin cohesive soil

IT Bahmed, J Khatti, KS Grover - Bulletin of Engineering Geology and the …, 2024 - Springer
This work introduces an optimal performance model for predicting the unconfined
compressive strength (UCS) of lime-stabilized soil using the machine (ensemble tree (ET) …

Estimation of unconfined compressive strength of marine clay modified with recycled tiles using hybridized extreme gradient boosting method

D Li, X Zhang, Q Kang, E Tavakkol - Construction and Building Materials, 2023 - Elsevier
An accurate evaluation of the clay's properties when mixed with recyclable materials is the
end objective of many geotechnical experimental efforts. However, experimental studies …

[HTML][HTML] Initial state of excavated soil and rock (ESR) to influence the stabilisation with cement

Y Lu, C Xu, A Baghbani - Construction and Building Materials, 2023 - Elsevier
This paper investigates the initial state of excavated soil and rock (ESR). These initial states
include dry density, organic content, water content (W c), cement content (C c), liquid index …

Optimized support vector machines combined with evolutionary random forest for prediction of back-break caused by blasting operation

Q Yu, M Monjezi, AS Mohammed, H Dehghani… - Sustainability, 2021 - mdpi.com
Back-break is an adverse event in blasting works that causes the instability of mine walls,
equipment collapsing, and reduction in effectiveness of drilling. Therefore, it boosts the total …

A precise neuro-fuzzy model enhanced by artificial bee colony techniques for assessment of rock brittleness index

M Parsajoo, DJ Armaghani, PG Asteris - Neural Computing and …, 2022 - Springer
When planning rock-based projects, the brittleness index (BI) may play a significant role in
the success of various projects, such as tunnel boring machines and road headers. Lack of …

Predicting rock displacement in underground mines using improved machine learning-based models

N Li, H Nguyen, J Rostami, W Zhang, XN Bui… - Measurement, 2022 - Elsevier
Displacement of rock mass in tunnels and underground mines is considered one of the most
hazardous phenomena that can cause the collapse of the structures. In this study, the rock …

Engineering and microstructural properties of alluvium clay stabilized with portland cement and coal bottom ash for sustainable future

M Hanafi, A Ekinci, E Aydin - KSCE Journal of Civil Engineering, 2022 - Springer
A massive amount of industrial waste is readily available for civil engineering works.
However, even a small amount can cause serious ecological problems. Global warming, on …