Research on SOFMNN in coal and gas outburst safety prediction

Hong Bin Guo*, Xiao Guang Yue, Ying Lu, Tarita Memonen, Fuyuan Xiao, Maia V. Cañiv

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

The mechanism of coal and gas outburst is still controversial, many occurrences of accidents have been a serious threat to people's life and property safety. In order to reduce the effect of coal and gas outburst disaster, the prediction of coal and gas outburst situation has a practical significance. Patent describing intelligent algorithms have been successfully applied in the prediction of coal and gas outburst. The self organizing feature mapping neural network is a high efficiency algorithm mechanism. Based on a comparison with the self organizing feature mapping neural network and improved colony clustering method, the accuracy rate of new algorithm is higher than the old method. This research is good for safety engineering development. The experiments performed demonstrate the effectiveness of the algorithm; this method has reference significance for the prediction of coal and gas outburst.

Original languageEnglish
Pages (from-to)55-61
Number of pages7
JournalRecent Patents on Computer Science
Volume9
Issue number1
DOIs
Publication statusPublished - 1 Apr 2016

Keywords

  • Coal and gas outburst
  • Intelligent algorithm
  • Safety engineering
  • Self organizing feature mapping neural network

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