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

  • Shuran L
  • Shujin L
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Abstract

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%.

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Shuran, L., & Shujin, L. (2011). Applying BP Neural Network Model to Forecast Peak Velocity of Blasting Ground Vibration. Procedia Engineering, 26, 257–263. https://doi.org/10.1016/j.proeng.2011.11.2166

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