Application of soft computing to predict blast-induced ground vibration

摘要: In this study, an attempt has been made to evaluate and predict the blast-induced ground vibration by incorporating explosive charge per delay distance from blast face monitoring point using artificial neural network (ANN) technique. A three-layer feed-forward back-propagation with 2-5-1 architecture was trained tested 130 experimental monitored records surface coal mines of Singareni Collieries Company Limited, Kothagudem, Andhra Pradesh, India. Twenty new data sets were used for validation comparison peak particle velocity (PPV) ANN conventional predictors. Results compared based on coefficient determination mean absolute error between predicted values PPV.