Application of two non-linear prediction tools to the estimation of tunnel boring machine performance

S Yagiz, C Gokceoglu, E Sezer, S Iplikci - Engineering Applications of …, 2009 - Elsevier
Predicting tunnel boring machine (TBM) performance is a crucial issue for the
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 …

[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 …

Indirect measure of shale shear strength parameters by means of rock index tests through an optimized artificial neural network

DJ Armaghani, M Hajihassani, BY Bejarbaneh, A Marto… - Measurement, 2014 - Elsevier
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 …

Implementing an ANN model optimized by genetic algorithm for estimating cohesion of limestone samples

M Khandelwal, A Marto, SA Fatemi, M Ghoroqi… - Engineering with …, 2018 - Springer
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 …

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 …

Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation

E Ghasemi, H Amini, M Ataei, R Khalokakaei - Arabian Journal of …, 2014 - Springer
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 …

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 …

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 …

Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique

R Mikaeil, SS Haghshenas, SS Haghshenas… - Neural Computing and …, 2018 - Springer
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 …