A novel dynamic predictive method of water inrush from coal floor based on gated recurrent unit model

Yonggang Zhang () and Lining Yang ()
Additional contact information
Yonggang Zhang: Tongji University
Lining Yang: China University of Mining and Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 105, issue 2, No 38, 2027-2043

Abstract: Abstract For water inrush from coal floor, due to different kinds of controlling factors and their internal correlations, the accuracy of prediction model is mostly below expectation. In this paper, it studies on which controlling factors should be selected for water inrush prediction model because all these factors have different influence on water inrush incidents based on the analysis of in situ data. Some factors are proved having limited impacts on water inrush, it is no necessary to collect in situ data of those factors from coal mining work face. Therefore, the workload and expense will decrease. In this paper, an index system of factors influencing water inrush from coal floor is established based on the current water inrush controlling theory and detailed analysis of in situ data obtained from mining regions. Following the Wrapper method in feature selection, 10 main controlling factors were selected from 14 existing indicators which were thought could affect water inrush. After training on dynamic GRU model which is made for water inrush prediction, a comparison among dynamic GRU model and stable SVM and BPMN models turns out the advantages of the previous with a higher accuracy in train, validation and test set against the latter. It is believed GRU model is able to predict water inrush water inrush from coal floor with high accuracy and hence enhances mining safety.

Keywords: Water inrush from coal floor; Feature selection; Gated recurrent unit neural network; Dynamic prediction (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-020-04388-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:105:y:2021:i:2:d:10.1007_s11069-020-04388-9

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-020-04388-9

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().