Prediction of Vibration Velocity Due to Blasting Using Artificial Neural Network
被引:0
作者:
Gao, Fuqiang
论文数: 0引用数: 0
h-index: 0
Gao, Fuqiang
Hou, Aijun
论文数: 0引用数: 0
h-index: 0
Hou, Aijun
机构:
来源:
PROGRESS IN CIVIL ENGINEERING, PTS 1-4
|
2012年
/
170-173卷
关键词:
Blasting vibration;
Artificial neural network;
Classic framework;
Coefficient of determination;
Sum of squares due to error;
D O I:
10.4028/www.scientific.net/AMM.170-173.3063
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
Vibration induced by blasting is one of the most hazardous events in the mining industry and may cause structural damage in country areas. Therefore, mitigating the possible hazard and predicting the vibration velocity is important. In this paper, an attempt has been made to predict the peak particle velocity using artificial neural network (ANN) by taking into consideration of maximum explosive charge used per delay and distance between blast face to monitoring point. To achieve the classic framework of this approach, the prediction results by artificial neural network were compared with measured values by coefficient of determination (CoD) and sum of squares due to error (SSE).