DocumentCode
3352972
Title
Evaluation Coupling Model of Mine Ventilation System Based on RS and ANN
Author
Fu Yuhua ; Dong Longjun
Author_Institution
Sch. of Resources & Safety Eng., Central South Univ., Changsha
fYear
2009
fDate
27-31 March 2009
Firstpage
1
Lastpage
4
Abstract
The broad masses of coal mining enterprises have been very concerned about how to effectively evaluate safety and reliability of mine ventilation system. Domestic and international scholars in this regard have also carried out a substantial amount of research and made a variety of different types of evaluation methods, but because there are many complex factors that affect the safety and reliability of mine ventilation system, it is very difficult to evaluate the ventilation system accurately using traditional methods. In view of this, this paper established an evaluation system based on rough sets and artificial neural network theory (ANN), it can complete a multi-level and multi-factor evaluation system and have self-learning capabilities. The coupling model is tested in actually projects, it shows that the model has a high accuracy, so that the model can be applied to the safety evaluation at the scene.
Keywords
coal; mining industry; neural nets; occupational safety; production engineering computing; reliability; ventilation; ANN; RS; artificial neural network; coal mining enterprises; evaluation coupling model; mine ventilation reliability; mine ventilation safety; mine ventilation system; multi-factor evaluation system; multi-level evaluation system; self-learning capabilities; Artificial neural networks; Domestic safety; Fans; Fuzzy systems; Layout; Reliability engineering; Rough sets; Set theory; Testing; Ventilation;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location
Wuhan
Print_ISBN
978-1-4244-2486-3
Electronic_ISBN
978-1-4244-2487-0
Type
conf
DOI
10.1109/APPEEC.2009.4918342
Filename
4918342
Link To Document