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[1]刘海滨,李光荣,刘 欢,等.基于ART-2人工神经网络的煤矿安全风险评价[J].中国安全生产科学技术,2014,10(2):81-85.[doi:10.11731/j.issn.1673-193x.2014.02.014]
　LIU Hai bin,LI Guang rong,LIU Huan,et al.Coal mine safety risk assessment based on ART2 neural network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2014,10(2):81-85.[doi:10.11731/j.issn.1673-193x.2014.02.014]
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基于ART-2人工神经网络的煤矿安全风险评价
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
10
期数:
2014年2期
页码:
81-85
栏目:
职业安全卫生管理与技术
出版日期:
2014-02-28

文章信息/Info

Title:
Coal mine safety risk assessment based on ART2 neural network
作者:
刘海滨1; 2;  李光荣2;  刘 欢2;  许静超2
（1煤炭资源与安全开采国家重点实验室，北京 100083；2中国矿业大学〈北京〉管理学院，北京 100083)
Author(s):
LIU Hai bin 1; 2;  LI Guang rong2;  LIU Huan2;  XU Jing chao2
(1. State Key Laboratory of Coal Resources and Safety Mining (CUMT), Beijing 100083, China;  2. Management School, China University of Mining & Technology (Beijing), Beijing 100083, China)
关键词:
煤矿安全; 风险评价; 神经网络; ART-2算法
Keywords:
coal mine safety;  risk assessment;  neural network;  ART2 algorithm
分类号:
X936
DOI:
10.11731/j.issn.1673-193x.2014.02.014
文献标志码:
A
摘要:
旨在为煤矿安全风险预控管理提供一种适用的风险评价模型或方法。研究过程中，介绍了人工神经网络自适应共振理论的ART-2算法；在安全系统工程理论及相关研究基础上，结合调研分析建立了风险评价指标体系；选取山西9家煤矿作为研究样本进行实证研究。该算法仿真识别结果与煤矿实际安全风险情况一致性程度达到7778%，表明针对煤矿安全风险预控管理过程中的安全风险评价，ART-2神经网络具有较好的适用性。
Abstract:
In order to find an applicative risk assessment model or method for coal mine safety risk precontrolling management, the ART2 artificial neural network algorithm was introduced, the safety system management theory was taken as foundation to establish a risk evaluation index system, and the security risk evaluation index datas of 9 coal mines were choosen as the research samples for simulation study. In the simulation results of ART2 algorithm, 7 of the 9 coals were consistent with the actual safety risk situation of coal mines. It showed that the ART2 neural network algorithm is an applicative method for coal mine risk assessment in the process of safety risk precontrolling management.

参考文献/References:

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备注/Memo

备注/Memo:
教育部重点科技项目（109032）；教育部新世纪优秀人才支持计划项目资助（NCET-10-772）；中央高校基本科研业务费项目资助（2009QG10）。
更新日期/Last Update: 2014-02-28