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Introducing stacking machine learning approaches for the prediction of rock deformation
Accurate and reliable predictions of rock deformations are crucial in many rock-based
projects in civil and mining engineering. In this research, a new system for the prediction of …
projects in civil and mining engineering. In this research, a new system for the prediction of …
A hybrid metaheuristic approach using random forest and particle swarm optimization to study and evaluate backbreak in open-pit blasting
Backbreak is a rock fracture problem that exceeds the limits of the last row of holes in an
explosion operation. Excessive backbreak increases operational costs and also poses a …
explosion operation. Excessive backbreak increases operational costs and also poses a …
Sustainable closed-loop supply chain network design with discount supposition
Supply chain network design (SCND) is one of the important, primary and strategic
decisions affecting competitive advantages and all other decisions in supply chain …
decisions affecting competitive advantages and all other decisions in supply chain …
[HTML][HTML] Prediction of UCS and CBR of microsilica-lime stabilized sulfate silty sand using ANN and EPR models; application to the deep soil mixing
Desert sands in Iran, which usually contain small amounts of silt and sulfate, do not have
significant strength, and thus, are not suitable for foundations or road construction. This …
significant strength, and thus, are not suitable for foundations or road construction. This …
Analytical model for soft rock tunnel with large deformation using stiff and yielding lining solutions
K Wu, M Sharifzadeh, Z Shao, X Zheng… - International Journal …, 2023 - ascelibrary.org
The mechanical responses of tunnels with stiff and yielding linings were predicted using an
analytical method. A theoretical model of a stiff lining-supported tunnel was established …
analytical method. A theoretical model of a stiff lining-supported tunnel was established …
Intelligent prediction of rock mass deformation modulus through three optimized cascaded forward neural network models
Rock mass deformation modulus (Em) is a key parameter that is needed to be determined
when designing surface or underground rock engineering constructions. It is not easy to …
when designing surface or underground rock engineering constructions. It is not easy to …
Cloud inversion analysis of surrounding rock parameters for underground powerhouse based on pso-bp optimized neural network and web technology
L Qu, HQ **e, JL Pei, YG Li, JM Wu, G Feng… - Scientific Reports, 2024 - nature.com
Aiming at the shortcomings of the BP neural network in practical applications, such as easy
to fall into local extremum and slow convergence speed, we optimized the initial weights and …
to fall into local extremum and slow convergence speed, we optimized the initial weights and …
Pipejacking clogging detection in soft alluvial deposits using machine learning algorithms
Abstract 'Clogging'is a common issue encountered during tunnelling in clayey soils which
can impede tunnel excavation, cause unplanned downtimes and lead to significant …
can impede tunnel excavation, cause unplanned downtimes and lead to significant …
A review: applications of fuzzy theory in rock engineering
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 …
behavior of rocks against internal and external factors. Fuzzy theory can be used to solve …
A hybrid approach of ANN and improved PSO for estimating soaked CBR of subgrade soils of heavy-haul railway corridor
The determination of subgrade/subsoil strength is one of the most important pavement
design factors in transportation engineering, particularly for railways, roadways, and airport …
design factors in transportation engineering, particularly for railways, roadways, and airport …