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Analysis of occupational accidents in underground and surface mining in Spain using data-mining techniques

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Sanmiquel Pera, LluísMés informacióMés informacióMés informació
Bascompta Massanes, MarcMés informacióMés informacióMés informació
Rossell Garriga, Josep MariaMés informacióMés informacióMés informació
Anticoi Sudzuki, Hernán FranciscoMés informació
Guasch Cascallo, EduardMés informacióMés informació
Document typeArticle
Defense date2018-03-07
Rights accessOpen Access
Attribution 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution 3.0 Spain
Abstract
An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the softwareWeka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained byWeka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.
CitationSanmiquel, L., Bascompta, M., Rossell, Josep M., Anticoi, H., Guasch, E. Analysis of occupational accidents in underground and surface mining in Spain using data-mining techniques. "International journal of environmental research and public health", 7 Març 2018, vol. 15, núm. 3 (462), p. 1-11. 
URIhttp://hdl.handle.net/2117/115140
DOI10.3390/ijerph15030462
ISSN1660-4601
Publisher versionhttp://www.mdpi.com/1660-4601/15/3/462
Collections
  • Departament d'Enginyeria Minera, Industrial i TIC - Articles de revista [282]
  • GREMS - Grup de Recerca en Mineria Sostenible - Articles de revista [106]
  • Departament de Matemàtiques - Articles de revista [2.895]
  • CoDAlab - Control, Modelització, Identificació i Aplicacions - Articles de revista [189]
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