Regression analysis and ANN models to predict rock properties from sound levels produced during drilling

This study aims to predict rock properties using soft computing techniques such as multiple regression, artificial neural network (MLP and RBF) models, taking drill bit speed, penetration rate, drill bit diameter and equivalent sound level produced during drilling as the input parameters. A database...

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Veröffentlicht in:	International journal of rock mechanics and mining sciences (Oxford, England : 1997) England : 1997), 2013-02, Vol.58, p.61-72
Hauptverfasser:	Rajesh Kumar, B., Vardhan, Harsha, Govindaraj, M., Vijay, G.S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Artificial neural network Buildings. Public works Density Drill bits Drilling Equivalent sound level Exact sciences and technology Geotechnics Learning theory Mathematical models Multi layer perceptron Multiple regression Neural networks Radial basis function Rock Rock drilling Rock properties Soil investigations. Testing Sound Strength of materials (elasticity, plasticity, buckling, etc.) Structural analysis. Stresses
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