Physico-mechanical rock properties are significant in all operational mining activities. This book evaluates rock properties by using empirical equations and soft computing techniques. It predicts various physico-mechanical properties such as uniaxial compressive strength (UCS), Schmidt rebound number (SRN), dry density, P-wave velocity (Vp), tensile strength (TS), Young's modulus (E), and percentage porosity (n) using multiple regression and artificial neural network (MLP and RBF) techniques, taking drill bit speed, penetration rate, drill bit diameter, and equivalent sound level produced during drilling as input parameters.
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