| 基于贝叶斯网络的某金属矿山风险分析 |
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| 引用本文： | 刘祖文,郭 云,詹 俊,张 念.基于贝叶斯网络的某金属矿山风险分析[J].有色金属(矿山部分),2016,68(2):84-86. |
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| 作者姓名： | 刘祖文 郭 云 詹 俊 张 念 |
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| 作者单位： | (1. 江西理工大学 建筑与测绘工程学院，江西 赣州 341000；2. 江西理工大学 资源与环境学院，江西 赣州 341000),(1. 江西理工大学 建筑与测绘工程学院，江西 赣州 341000；2. 江西理工大学 资源与环境学院，江西 赣州 341001),(1. 江西理工大学 建筑与测绘工程学院，江西 赣州 341000；2. 江西理工大学 资源与环境学院，江西 赣州 341002),(1. 江西理工大学 建筑与测绘工程学院，江西 赣州 341000；2. 江西理工大学 资源与环境学院，江西 赣州 341003) |
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| 摘 要： | 为了使金属矿山安全管理人员能更有效地对矿山进行风险管理。通过对采矿区间事故数据的统计,依据事故后果严重程度确定其权重值,建立矿山事故灾害事故树模型,并将其转换为贝叶斯网络,对各类生产事故条件概率进行计算。将计算结果与矿山其后几年生产事故数据进行比较,该风险分析模型能有效对矿山事故进行分析。
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| 关 键 词： | 金属矿山 风险分析 事故树分析 贝叶斯网络 |
| 收稿时间： | 2015/9/11 0:00:00 |
| 修稿时间： | 2015/9/18 0:00:00 |
Risk analysis of a metal mine based on Bayesian Network |
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| Authors: | LIU Zuwen GUO Yun ZHAN Jun and ZHANG Nian |
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| Affiliation: | (1. School of Architectural and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China; 2. School of Resources and Environment Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China),(1. School of Architectural and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China; 3. School of Resources and Environment Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China),(1. School of Architectural and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China; 4. School of Resources and Environment Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China) and (1. School of Architectural and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China; 5. School of Resources and Environment Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China) |
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| Abstract: | In order to metal mine safety management personnel can make risk analysis be more effectively. Based on the data collection of mining accidents, ensure the weight value by accident severity consequences, established the mine accident Fault Tree Model, and turn it to Bayesian Network, then calculate probability calculation of production accidents. To compare calculated results with accident data of the next few years in mines production, sure that the risk analysis model can analyze the mine accident effectively. |
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| Keywords: | metal mine risk analysis accident tree analysis Bayesian Network |
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