Automatic Classification of Microseismic Events With Similar Features and Noise Interference Using RSREL-stacking

Microseismic events must be classified to obtain effective disaster precursor information. To further improve the accuracy and efficiency of microseismic event classification, and based on the microseismic data of rockburst monitoring, combined with time-frequency analysis theory, the main factors a...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2024-01, Vol.62, p.1-1
Hauptverfasser:	Zhang, Zhen, Ye, Yicheng, Zhang, Guangquan, Zhu, Quanjie, Luo, Xiaobing, Fen, Jie
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Classification Classification of microseismic events Data mining Deep learning Disasters Feature extraction Frequency analysis Frequency dependence image feature extraction Image segmentation Interference Microseisms Monitoring R-HOG Rockbursts Seismic activity Spectrogram Stacking stacking integrated model Time-frequency analysis Visual Geometry Group 16 (VGG16)
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