Deep learning and heterogeneous signal fusion approach to precursor feature recognition and early warning of coal and gas outburst

Author:

Li Bing,Wang Enyuan,Shang Zheng,Liu Xiaofei,Li Zhonghui,Dong Jun

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,General Chemical Engineering,Environmental Chemistry,Environmental Engineering

Reference73 articles.

1. Evidential framework for data fusion in a multi-sensor surveillance system;Andre;Eng. Appl. Artif. Intell.,2015

2. Ban Q. Study on Precursor Law of AE-EMR-GAS and Early-warning Technology of Outburst in Yizhong Coal Mine. vol. China University of Mining and Technology 2015.

3. Dynamic prediction of coal and gas outburst based on multi-factor pattern recognition;Bi;J. Saf. Sci. Technol.,2017

4. Power spectral models of stationary earthquake-induced ground motion process considering site characteristics;Chen;Emerg. Manag. Sci. Technol.,2022

5. Early warning of coal and gas outburst based on peak-to-valley ratio method of electromagnetic radiation;Chen;J. Saf. Sci. Technol.,2019

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