Prediction of Safe Charge to Protect Surrounding Structures Using Support Vector Machine

The present paper mainly with deals the prediction of safe explosive charge used per delay (Q_MAX) using support vector machine (SVM) incorporating peak particle velocity (PPV) and distance between blast face to monitoring point (D). 150 blast vibration data sets were monitored at different vulnerable and strategic locations in and around a major coal producing opencast coal mines in India. 120 blast vibrations records were used for the training of the SVM model vis-à-vis to determine site constants of various conventional vibration predictors. Rest 30 new randomly selected data sets were used to compare the SVM prediction results with widely used conventional predictors. Results were compared based on coefficient of correlation (R) between measured and predicted values of safe charge of explosive used per delay (Q_MAX). It was found that coefficient of correlation between measured and predicted Q_MAX by SVM was 0.997, whereas it was ranging from 0.063 to 0.872 by different conventional predictor equations.