期刊
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
卷 69, 期 4, 页码 599-606出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s10064-010-0301-3
关键词
Artificial neural networks; Rock properties; Strength parameters
资金
- CSIR, New Delhi
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.
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