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Bulletin of Engineering Geology and the Environment

Erschienen in:

01.11.2010 | Original Paper

Estimation of strength parameters of rock using artificial neural networks

verfasst von: Kripamoy Sarkar, Avyaktanand Tiwary, T. N. Singh

Erschienen in: Bulletin of Engineering Geology and the Environment | Ausgabe 4/2010

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Abstract

The 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.

Vorheriger Artikel Comparison of the geotechnical properties of crushed shales from Southeastern Nigeria

Nächster Artikel Microscopic analysis of the engineering geological behavior of soft clay in Shanghai, China

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Titel: Estimation of strength parameters of rock using artificial neural networks
verfasst von: Kripamoy Sarkar
Avyaktanand Tiwary
T. N. Singh
Publikationsdatum: 01.11.2010
Verlag: Springer-Verlag
Erschienen in: Bulletin of Engineering Geology and the Environment / Ausgabe 4/2010
Print ISSN: 1435-9529
Elektronische ISSN: 1435-9537
DOI: https://doi.org/10.1007/s10064-010-0301-3

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