Application of soft computing to predict blast-induced ground vibration

Engineering with Computers - Tập 27 - Trang 117-125 - 2009
Manoj Khandelwal1, D. Lalit Kumar2, Mohan Yellishetty3
1Department of Mining Engineering, College of Technology and Engineering, Maharana Pratap University of Agriculture and Technology, Udaipur, India
2Singareni Collieries Company Limited, Kothagudem, India
3Department of Civil Engineering, Monash University, Melbourne, Australia

Tóm tắt

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

Tài liệu tham khảo

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