A correlational research on developing an innovative integrated gas warning system: a case study in ZhongXing, China

A correlational research on developing an innovative integrated gas warning system: a case study in ZhongXing, China

Gas explosions and outbursts were the leading types of gas accidents in mining in China with gas concentration exceeding the threshold limit value (TLV) as the leading cause. Current research is focused mainly on using machine learning approaches for avoiding exceeding the TLV of the gas concentrati...

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Enregistré dans:
Détails bibliographiques
Auteurs principaux: Robert M. X. Wu, Wanjun Yan, Zhongwu Zhang, Jinwen Gou, Jianfeng Fan, Bao Liu, Yong Shi, Bo Shen, Haijun Zhao, Yanyun Ma, Jeffrey Soar, Xiangyu Sun, Ergun Gide, Zhigang Sun, Peilin Wang, Xinxin Cui, Ya Wang
Format: article
Langue:EN
Publié: Taylor & Francis Group 2021
Sujets:
case study
correlational research
gas monitoring system
machine learning
warning system
Environmental technology. Sanitary engineering
TD1-1066
Environmental sciences
GE1-350
Risk in industry. Risk management
HD61
Accès en ligne:https://doaj.org/article/1a9f36c461b14280ab660172c33d6b1c
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https://doaj.org/article/1a9f36c461b14280ab660172c33d6b1c

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