Abstract
Forecasting model of the rate of rock burst acoustic emission time series has been established by BP neural network, and it is combined with the catastrophe theory to determine whether the rock burst. And then the experimental data recorded are used for examining the model. The results show that the degree of prediction accuracy is high, and it proves that the prediction model of rock burst is feasible.
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Xu, Y., Xu, D. (2010). The Study of Forecasting Model of Rock Burst for Acoustic Emission Based on BP Neural Network and Catastrophe Theory. In: Zeng, Z., Wang, J. (eds) Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12990-2_2
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DOI: https://doi.org/10.1007/978-3-642-12990-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12989-6
Online ISBN: 978-3-642-12990-2
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