Prediction of time-energy-location of microseismic events induced by deep coal-energy mining: Deep learning approach-Reference-Cited by-同舟云学术

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Prediction of time-energy-location of microseismic events induced by deep coal-energy mining: Deep learning approach

Published:2024-06 Issue: Volume: Page:
ISSN:1674-7755
Container-title:Journal of Rock Mechanics and Geotechnical Engineering
language:en
Short-container-title:Journal of Rock Mechanics and Geotechnical Engineering

Author:

Song Yue,Wang Enyuan,Yang Hengze,Chen Dong,Li Baolin,Di Yangyang

Funder

Key Technologies Research and Development Program

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference40 articles.

1. Quantitative analysis of seismic velocity tomography in rock burst hazard assessment;Cai;Nat. Hazards,2015

2. STGCN for modeling vehicle trajectory in highway scenario;Chen,2020

3. A quantitative pre-warning for coal burst hazardous zones in a deep coal mine based on the spatio-temporal forecast of microseismic events;Chen;Process Saf. Environ. Protect.,2022

4. ConvLSTM for Predicting short-term spatiotemporal distribution of seismic risk induced by large-scale coal mining;Chen;Nat. Resour. Res.,2023

5. Locating leaking buried pipes based on ground microseismic records in 3D space;Cheng;Surv. Geophys.,2018

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