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Adaptive Pattern Recognition to Predict Rockbursts in Underground Openings

Feng Xiating  
With the neural network system theory applied to the prediction for probable rockbursts in underground opening,an adaptive pattern recognition is developed the way the rockburst pattern features are collected from previous cases in combination with expertises so as to set up I/O pattern pairs. Nonlinear mapping between various input patterns and their output patterns is thus established by self-learning of neural network and extrapolated. It is proved that the network and values of weights after learning are available to the identification of rockburst intensity for a new type of rock. The results show that this method is scientific and reliable.
【Fund】: 辽宁省博士启动基金
【CateGory Index】: TU457
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