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Estimation of strength parameters of rock using artificial neural networks

dc.contributor.authorSarkar K.; Tiwary A.; Singh T.N.
dc.date.accessioned2025-05-24T09:58:19Z
dc.description.abstractThe accurate determination of geomechanical properties such as uniaxial compressive strength and shear strength requires considerable time in collecting appropriate samples, their preparation and laboratory testing. To minimize the time and cost, a number of empirical relations have been reported which are widely used for the estimation of complex rock properties from more easily acquired data. This paper reports the use of an artificial neural network to predict the deformation properties of Coal Measure rocks using dynamic wave velocity, point load index, slake durability index and density. The results confirm the applicability of this method. © 2010 Springer-Verlag.
dc.identifier.doihttps://doi.org/10.1007/s10064-010-0301-3
dc.identifier.urihttp://172.23.0.11:4000/handle/123456789/23149
dc.relation.ispartofseriesBulletin of Engineering Geology and the Environment
dc.titleEstimation of strength parameters of rock using artificial neural networks

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