Estimation of the Rock Deformation Modulus and RMR Based on Data Mining Techniques

In this work Data Mining tools are used to develop new and innovative models for the estimation of the rock deformation modulus and the Rock Mass Rating (RMR). A database published by Chun et al. (Int J Rock Mech Min Sci 46:649–658, 2008) was used to develop these models. The parameters of the datab...

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Bibliographic Details
Published in:Geotechnical and geological engineering 2012-08, Vol.30 (4), p.787-801
Main Authors: Martins, Francisco F., Miranda, Tiago F. S.
Format: Article
Language:English
Subjects:
Algorithms
Civil Engineering
Compressive strength
Data analysis
Data mining
Deformation
Earth and Environmental Science
Earth Sciences
Geotechnical Engineering & Applied Earth Sciences
Groundwater
Hydrogeology
Mathematical models
Modulus of deformation
Orientation
Original Paper
Parameters
Rock deformation
Rock mass rating
Rocks
Terrestrial Pollution
Waste Management/Waste Technology
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Summary:In this work Data Mining tools are used to develop new and innovative models for the estimation of the rock deformation modulus and the Rock Mass Rating (RMR). A database published by Chun et al. (Int J Rock Mech Min Sci 46:649–658, 2008) was used to develop these models. The parameters of the database were the depth, the weightings of the RMR system related to the uniaxial compressive strength, the rock quality designation, the joint spacing, the joint condition, the groundwater condition and the discontinuity orientation adjustment, the RMR and the deformation modulus. As a modelling tool the R program environment was used to apply these advanced techniques. Several algorithms were tested and analysed using different sets of input parameters. It was possible to develop new models to predict the rock deformation modulus and the RMR with improved accuracy and, additionally, allowed to have an insight of the importance of the different input parameters.
ISSN:0960-3182
1573-1529
DOI:10.1007/s10706-012-9498-1