首页|Predicting microseismic,acoustic emission and electromagnetic radiation data using neural networks
Predicting microseismic,acoustic emission and electromagnetic radiation data using neural networks
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万方数据
维普
Microseism,acoustic emission and electromagnetic radiation(M-A-E)data are usually used for pre-dicting rockburst hazards.However,it is a great challenge to realize the prediction of M-A-E data.In this study,with the aid of a deep learning algorithm,a new method for the prediction of M-A-E data is proposed.In this method,an M-A-E data prediction model is built based on a variety of neural networks after analyzing numerous M-A-E data,and then the M-A-E data can be predicted.The predicted results are highly correlated with the real data collected in the field.Through field verification,the deep learning-based prediction method of M-A-E data provides quantitative prediction data for rockburst monitoring.
万方数据
维普
