Safety assessment method and its application of complex dynamic ventilation network

摘要：

There are so many fuzzy factors that affect the safety of mine ventilation system, and the data acquired from monitoring systems was so large that it is very difficult to evaluate the ventilation system accurately while using traditional methods. In order to solve the problem, a safety evaluation model was established based on fuzzy neural networks and rough set theory. It can not only complete a multi-level and multi-factor evaluation system also have selflearning capabilities, the verification of the evaluation model shows that the model has a high accuracy, and the total error is only 0.037, so that the model can be applied to the safety evaluation of complex dynamic network.

关键词： ventilation risk assessment fuzzy neural networks rough set theory

作者: ZHU Chuanjie LIN Baiquan

作者单位: State key Laboratory of Coal Resources and Safe Mining & Faculty of Safety Engineering China University of Mining & Technology Xuzhou, china

会议类型: 国际会议

会议名称: 2011 International Conference on Security Science and Technology(ICSST 2011) (2011年安全科学与技术国际会议)

会议地点: 重庆

会议语种:英文

页码: 229-233

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）