ID (ISN) del documento | 112057 |
Número CIS |
11-0706 |
ISSN - Título de la serie |
0925-7535 - Safety Science |
Año |
2011 |
Número de serie |
|
Autor(es) |
Cheng J., Yang S. |
Título |
Data mining applications in evaluating mine ventilation system |
Información bibliográfica |
2011, 5p. Illus. 15 ref. |
Acceso Internet |
Data_mining_applications.pdf [en inglés]
|
Resumen |
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. |
Descriptores (primarios) |
explotación minera en el fondo; valoración del riesgo; sistemas de ventilación; sistemas de alarma; mineria del carbón |
Descriptores (secundarios) |
modelos matemáticos; fiabilidad; descripción del procedimiento |
Tipo de documento |
D - Artículos periódicos |
Tema(s) |
Minas y canteras Organización de la seguridad, formación, educación
|
Broad subject area(s) |
Riesgos mecánicos, transporte
|
Navegación por categoria(s) |
Ventilation Risk evaluation Mining and quarrying
|