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Management of methane emission in coal mines using artificial neural networks: A systematic review
1 School of Economics and Management, Anhui University of Science and Technology, Huainan, China.
2 School of Civil Engineering and Architecture, Anhui University of Science and Technology, Huainan, China.
3 School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, China.
Review
International Journal of Science and Research Archive, 2024, 11(02), 1387–1404.
Article DOI: 10.30574/ijsra.2024.11.2.0579
Publication history:
Received on 25 February 2024; revised on 06 April 2024; accepted on 09 April 2024
Abstract:
Underground mines are responsible for a large number of the released methane worldwide. Our study paper can contribute to mitigating methane emissions, hence reducing the concentration about greenhouse emissions within the environment and mitigating the associated hazardous risks. In this study, more than 45 recent journals on Methane emission in Coal Mines were gathered from Web of Science, IEEE Xplore, ScienceDirect, and ResearchGate. A systematic review is accomplished of the past four years of various parts of Methane gas emission such as anthropogenic emission sources, gas emissions detection, prediction of methane using different technology and the Artificial intelligence projection model for methane emission. The outcomes reveal that since the methane emission management has obtained increasing attention over the past four years. This study also shows that big countries are using technology to control and utilize the methane emission to reduce the energy crisis. To decrease the coal mine injuries, academic understanding of underground methane management has increased, different technologies are integrated and support from various IT departments has amplified for the forecasting. In the future, the most critical task for coal mines risk assessment is to restore the worker's trust in mine safety, and the primary solution is to give more awareness to the underground management and workers through utilizing Artificial Intelligence (AI) mainly Artificial Neural Networks (ANN).
Keywords:
Coal mining; Methane emission; ANN; Risk assessment; Energy waste; Artificial intelligence
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
