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Study of Spanish mining accidents using data mining techniques

Author
Sanmiquel, L.; Rossell, Josep M.; Vintro, C.
Type of activity
Journal article
Journal
Safety science
Date of publication
2015-06
Volume
75
First page
49
Last page
55
DOI
https://doi.org/10.1016/j.ssci.2015.01.016 Open in new window
Repository
http://hdl.handle.net/2117/26427 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S092575351500017X Open in new window
Abstract
Mining is an economic sector with a high number of accidents. Mines are hazardous places and workers can suffer a wide variety of injuries. Utilizing a database composed of almost 70,000 occupational accidents and fatality reports corresponding to the decade 2003–2012 in the Spanish mining sector, the paper analyzes the main causes of those accidents. To carry out the study, powerful statistical tools have been applied, such as Bayesian classi¿ers, decision trees or contingency t...
Citation
Sanmiquel, L.; Rossell, Josep M.; Vintro, C. Study of Spanish mining accidents using data mining techniques. "Safety science", Juny 2015, vol. 75, p. 49-55.
Keywords
Bayesian network, Classification methods, Data mining, Mining accidents
Group of research
CoDAlab - Control, Dynamics and Applications
GREMS - Sustainable Mining Research Group
OPE-PROTHIUS -
SSR-UPC - Smart Sustainable Resources

Participants