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...
Enregistré dans:
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: | |
Accès en ligne: | https://doaj.org/article/1a9f36c461b14280ab660172c33d6b1c |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Creating resilient communities with medium-range hazard warning systems
par: Bapon (SHM) Fakhruddin, et autres
Publié: (2021) -
A genetic researcher’s devil’s dilemma: Warn relatives about their genetic risk or respect confidentiality agreements with research participants?
par: Lieke M. van den Heuvel, et autres
Publié: (2021) -
Harnessing the Challenges and Solutions to Improve Security Warnings: A Review
par: Zarul Fitri Zaaba, et autres
Publié: (2021) -
Research on Early Warning for Gas Risks at a Working Face Based on Association Rule Mining
par: Yuxin Huang, et autres
Publié: (2021) -
Method for Environmental Flows Regulation and Early Warning with Remote Sensing and Land Cover Data
par: Yuming Lu, et autres
Publié: (2021)