Statistical Analysis of the Capabilities of Various Pattern Recognition Algorithms for Fracture Detection Based on Monitoring Drilling Parameters

Ground conditions, including characteristics of fractures, joints, bed separations, and strengths of rock layers, are critical factors for proper design of openings in underground mining and construction projects. Correct understanding of geologic conditions allows for improvement and optimization o...

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Bibliographic Details
Published in:	Rock mechanics and rock engineering Vol. 53; no. 5; pp. 2265 - 2278
Main Authors:	Liu, Wenpeng, Rostami, Jamal, Ray, Asok, Elsworth, Derek
Format:	Journal Article
Language:	English
Published:	Vienna Springer Vienna 01.05.2020 Springer Nature B.V
Subjects:	Algorithms Apertures Civil Engineering Computer simulation Construction industry Data analysis Design factors Design optimization Detection Drilling Earth and Environmental Science Earth Sciences Fractures Geology Geophysics/Geodesy Joints (timber) Laboratories Laboratory tests Monitoring Original Paper Parameters Pattern recognition Project engineering Rock bolts Rock excavation Rocks Statistical analysis Statistical methods Statistics Underground construction Underground mining Voids Composite drilling parameters Pattern recognition algorithm Fracture detection Instrumented roof bolter Inclined joints Field penetration index (FPI)
ISSN:	0723-2632, 1434-453X
Online Access:	Get full text
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