DocumentCode :
1807509
Title :
Regional forecast of deep seam mining floor water-bursting based on fuzzy cluster analysis and fuzzy pattern recognition
Author :
Shuangyue Liu ; Lina Chen ; Juan Wang ; Dan Wang ; Fei Jiang
Author_Institution :
Department of Civil & Environment Engineering, University of Science & Technology Beijing, 10083, China
fYear :
2013
fDate :
1-8 Jan. 2013
Firstpage :
1
Lastpage :
4
Abstract :
Recurring to well-rounded fuzzy theory and technology can realize exact expression and manage between imprecise information and imprecise relation on water-bursting prediction. Advanced a method combining the fuzzy cluster analysis and fuzzy pattern recognition to forecast deep seam mining floor water-bursting. Firstly, the simple integration is classified for the water-bursting by adopting clustering analysis method. The fuzzy model is set up for different degree. Afterwards, the danger degree of the undetermined forecasting sample is predicted by applying fuzzy pattern recognition. Through actual validation, the reliability of the prediction is tested and verified.
Keywords :
Coal; Face; Floors; Forecasting; Indexes; Pattern recognition; Stress; deep seam mining floor water-bursting; fuzzy cluster analysis; fuzzy pattern recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Conference Anthology, IEEE
Conference_Location :
China
Type :
conf
DOI :
10.1109/ANTHOLOGY.2013.6785047
Filename :
6785047
Link To Document :
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