Application of two non-linear prediction tools to the estimation of tunnel boring machine performance
Predicting tunnel boring machine (TBM) performance is a crucial issue for the
accomplishment of a mechanical tunnel project, excavating via full face tunneling machine …
accomplishment of a mechanical tunnel project, excavating via full face tunneling machine …
Predicting intact rock strength for mechanical excavation using multivariate statistics, artificial neural networks, and regression trees
B Tiryaki - Engineering Geology, 2008 - Elsevier
Mechanical rock excavation projects require uniaxial compressive strength (UCS) and static
modulus of elasticity (E) of the intact rock material. High-quality core specimens of proper …
modulus of elasticity (E) of the intact rock material. High-quality core specimens of proper …
[PDF][PDF] Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach.
M Monjezi, H Amini Khoshalan… - Arabian Journal of …, 2012 - academia.edu
An ideally performed blasting operation enormously influences the mining overall cost. This
aim can be achieved by proper prediction and attenuation of flyrock and backbreak. Poor …
aim can be achieved by proper prediction and attenuation of flyrock and backbreak. Poor …
Indirect measure of shale shear strength parameters by means of rock index tests through an optimized artificial neural network
Shear strength is one of the most important features in engineering design of geotechnical
structures such as embankments, earth dams, tunnels and foundations. Shear strength …
structures such as embankments, earth dams, tunnels and foundations. Shear strength …
Implementing an ANN model optimized by genetic algorithm for estimating cohesion of limestone samples
Shear strength parameters such as cohesion are the most significant rock parameters which
can be utilized for initial design of some geotechnical engineering applications. In this study …
can be utilized for initial design of some geotechnical engineering applications. In this study …
Prediction of rock fragmentation due to blasting using artificial neural network
A Bahrami, M Monjezi, K Goshtasbi… - Engineering with …, 2011 - Springer
Prediction of rock fragmentation is essential for optimizing blasting operation. Fragmentation
depends on many parameters such as rock mass properties, blast geometry and explosive …
depends on many parameters such as rock mass properties, blast geometry and explosive …
Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation
Flyrock arising from blasting operations is one of the crucial and complex problems in
mining industry and its prediction plays an important role in the minimization of related …
mining industry and its prediction plays an important role in the minimization of related …
Evaluation of rock property variability
AE Aladejare, Y Wang - … : Assessment and Management of Risk for …, 2017 - Taylor & Francis
Rocks are natural geo-materials, whose properties are affected by many spatially-varying
factors, such as the properties of their parent materials, weathering processes, and …
factors, such as the properties of their parent materials, weathering processes, and …
Evaluation of shear strength parameters of rocks by preset angle shear, direct shear and triaxial compression tests
F Gong, S Luo, G Lin, X Li - Rock Mechanics and Rock Engineering, 2020 - Springer
Estimation of shear strength parameters, which are generally known as the cohesion and
internal friction angle (c and φ) in the Mohr–Coulomb (M–C) strength criterion, plays an …
internal friction angle (c and φ) in the Mohr–Coulomb (M–C) strength criterion, plays an …
Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique
The purpose of this study is the application of meta-heuristic algorithms and fuzzy logic in
the optimization and clustering to predict the sawability of dimension stone. Survey and …
the optimization and clustering to predict the sawability of dimension stone. Survey and …