| Document ID (ISN) | 112057 |
| CIS number |
11-0706 |
| ISSN - Serial title |
0925-7535 - Safety Science |
| Year |
2011 |
| Convention or series no. |
|
| Author(s) |
Cheng J., Yang S. |
| Title |
Data mining applications in evaluating mine ventilation system |
| Bibliographic information |
2011, 5p. Illus. 15 ref. |
| Internet access |
Data_mining_applications.pdf [in English]
|
| Abstract |
Ventilation systems are an important component of underground mines. They provide a sufficient quantity of air to maintain suitable working environment. Based on former findings and in-depth analysis of mine ventilation systems, this article proposes an early warning model to improve the mine ventilation safety. The model itself is comprised of two sub-models, and two data mining techniques are used to assist in building each sub-model. One is the optimal indexes selection model which applies the Rough Set theory (RS) to assist the selection of best ventilation indexes. The other is the risk evaluation model based on the Support Vector Machine (SVM) to classify the risk ranks for the mine ventilation system. Testing cases are used to demonstrate the applicability of this integrated model. |
| Descriptors (primary) |
underground mining; hazard evaluation; ventilation systems; alarm systems; coal mining |
| Descriptors (secondary) |
mathematical models; reliability; description of technique |
| Document type |
D - Periodical articles |
| Subject(s) |
Mines and quarries
Safety organization and training
|
| Broad subject area(s) |
Mechanical hazards, transport
|
| Browse category(ies) |
Ventilation
Risk evaluation
Mining and quarrying
|
