Applying BP Neural Network Model to Forecast Peak Velocity of Blasting Ground Vibration

摘要：

The control of blasting ground vibration has been an important research subject in engineering blasting field, and the accurate forecast of blasting vibration is the premise and basis of vibrating control. BP neural network is a neural network model that is most widely used in non-linear forecast. A BP neural network model was established for forecasting the blasting vibration speed. The analyses show that the mean error of blasting vibration speed is 5.7％. As a result, the neural network forecast model obtains higher accuracy, compared with common linear recession method which the mean error is 20.7％.

关键词： BP neural network Blasting vibration Forecast

作者: Lv Shuran Lv Shujin

作者单位: School of Safty and Environmental Engineering, Capital University of Economics and Business, Beijing The Mathematic and Computer Departmen, Baoding University,Hebei 071000,China

会议类型: 国际会议

会议名称: The First International Symposium on Mine Safety Science and Engineering (首届矿山安全科学与工程学术会议)

会议地点: 北京

会议语种:英文

页码: 260-267

在线出版日期: 2011-10-27（万方平台首次上网日期，不代表论文的发表时间）