EconPapers    
Economics at your fingertips  
 

A new prediction model for mining subsidence deformation: the arc tangent function model

Lei Nie, Hongfei Wang (), Yan Xu and Zechuang Li

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 75, issue 3, 2185-2198

Abstract: Ground subsidence in underground coal mining areas causes environmental damage and creates hazards on the ground surface, which is long-term, widely distributed, and can lead to large-scale geological disasters. Achieving a high-precision method to predict mining subsidence deformation is very important for assessing environmental damage and countermeasures. In this paper, based on the “S”-type settlement curves of the monitoring points in the collapsed pit and the failure mechanism of rock strata on the goaf, the arc tangent function model was proposed and applied to the Taihe coal mine in Fushun, Liaoning Province, China. Using the Levenberg–Marquardt algorithm for nonlinear curve fitting of the data, the parameters of the model are obtained, and extending it in time, the prediction function will be obtained. Using different monitoring data to validate the model shows that the accuracy of the medium- and short-term forecasting is very good. With continuous updating of the monitoring data, the forecasting achieves higher accuracy and the function of dynamic track forecasting is achieved. A very high correlation coefficient was obtained (0.996) using all the available data from the monitoring point for the best-fit curve. This prediction model provides a reference for the evaluation and treatment of ground subsidence in the Taihe coal mining area. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Ground subsidence; Geological disasters; Arc tangent function; “S”-type settlement curve; Dynamic track forecasting (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11069-014-1421-z (text/html)
Access to full text is restricted to subscribers.

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:75:y:2015:i:3:p:2185-2198

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

DOI: 10.1007/s11069-014-1421-z

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 ().

 
Page updated 2025-03-20
Handle: RePEc:spr:nathaz:v:75:y:2015:i:3:p:2185-2198