Research on Forecast Method of Coal Mine Emergencies Base on Rough Sets-Neural Network and Case-based Reasoning

Author

Liu Shuanhong ; Shao Liangshan ; Lu Lin

Author_Institution

Inst. of Syst. Eng., Liaoning Tech. Univ., Huludao, China

fYear

2013

fDate

16-18 Jan. 2013

Firstpage

1171

Lastpage

1174

Abstract

The method based on rough sets-neural network and case-based reasoning is provided to forecast coal mine´s emergencies in view of the characteristics of coal mine emergencies and feature knowledge base of coal mine accidents is established. The combinations have complementary advantages with each other. Finally, taking gas disasters as an example, it shows that the method for coal mine accident prevention and rescue work can provide effective decision support and practical operability.

Keywords

accident prevention; case-based reasoning; coal; emergency services; mining industry; neural nets; rough set theory; case-based reasoning; coal mine accident prevention; coal mine emergency; coal mine rescue work; feature knowledge base; forecast method; gas disaster; rough sets-neural network; Biological neural networks; Coal mining; Cognition; Data mining; Data models; Training; Case-based reasoning; Data mining; Emergencies; Neural network; Rough set;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4673-4893-5

Type

conf

DOI

10.1109/ISDEA.2012.276

Filename

6455967