Analysis of Coal Mine Hidden Danger Correlation Based on Improved A Priori Algorithm

This paper outlines an improved Apriori algorithm that suits coal mine hidden danger data. Then preprocess the data according to the characteristics of safety hidden danger data of coal mine workplaces, including data import and extraction. Put this algorithm embedded in a coal mine hidden danger in...

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Bibliographic Details
Published in2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications pp. 112 - 116
Main Authors Liu Shuangyue, Peng Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2013
Subjects
Algorithm design and analysis
Association rules
Coal mining
Face
LabVIEW
Safety
Virtual Instrument
Online AccessGet full text
DOI10.1109/ISDEA.2013.431

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Summary:This paper outlines an improved Apriori algorithm that suits coal mine hidden danger data. Then preprocess the data according to the characteristics of safety hidden danger data of coal mine workplaces, including data import and extraction. Put this algorithm embedded in a coal mine hidden danger investigation system. After this is coal mine hidden danger data association rules mining based on the improved Apriori algorithm to achieve getting valuable association rules inside the coal mine hidden dangers. Provide recommendations for improvement for enterprises in the hidden danger management and prevention and ultimately there is an important practical significance in preventing accidents and reducing the loss of the accidents.
DOI:10.1109/ISDEA.2013.431