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. (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 (UCS), the rock quality designation (RQD), the joint spacing (JS), the joint condition (JC), the groundwater condition (GWC) and the discontinuity orientation adjustment (DOA), 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 parameter...
The evaluation of geomechanical parameters for rock masses is one of the issues with largest uncerta...
The deformation modulus of rock masses (E m) is one of the significant parameters required to build ...
In recent years, several soft computing models have been proposed to estimate the elastic modulus of...
Due to the inherent geological complexity and characterization difficulties in rock formations, the ...
Empirical classification systems like the RMR and Q are often used in current practice of geotechni...
The rock mass deformation modulus (Em) is an essential input parameter in numerical modeling for ass...
Due to the inherent geological complexity and characterisation difficulties in rock formations, the...
Abstract Deformation modulus of rock mass is one of the input parameters to most rock engineering d...
The determination of mechanical properties of granitic rocks has a great importance to solve many en...
Data Mining (DM) techniques have been successfully used in many fields and more recently also in geo...
Summary. Data Mining (DM) techniques have been successfully used in many fields and more recently al...
Rock Classification methods are important for the evaluation of different rock parameters to be adop...
A generic rock mass database consisting of 9 parameters is compiled from 225 studies. The 9 paramete...
The evaluation of geomechanical parameters for rock masses is one of the issues with largest uncert...
Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide i...
The evaluation of geomechanical parameters for rock masses is one of the issues with largest uncerta...
The deformation modulus of rock masses (E m) is one of the significant parameters required to build ...
In recent years, several soft computing models have been proposed to estimate the elastic modulus of...
Due to the inherent geological complexity and characterization difficulties in rock formations, the ...
Empirical classification systems like the RMR and Q are often used in current practice of geotechni...
The rock mass deformation modulus (Em) is an essential input parameter in numerical modeling for ass...
Due to the inherent geological complexity and characterisation difficulties in rock formations, the...
Abstract Deformation modulus of rock mass is one of the input parameters to most rock engineering d...
The determination of mechanical properties of granitic rocks has a great importance to solve many en...
Data Mining (DM) techniques have been successfully used in many fields and more recently also in geo...
Summary. Data Mining (DM) techniques have been successfully used in many fields and more recently al...
Rock Classification methods are important for the evaluation of different rock parameters to be adop...
A generic rock mass database consisting of 9 parameters is compiled from 225 studies. The 9 paramete...
The evaluation of geomechanical parameters for rock masses is one of the issues with largest uncert...
Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide i...
The evaluation of geomechanical parameters for rock masses is one of the issues with largest uncerta...
The deformation modulus of rock masses (E m) is one of the significant parameters required to build ...
In recent years, several soft computing models have been proposed to estimate the elastic modulus of...