煤矿安全隐患治理能力评估与预测方法研究
发布时间：2018-10-12 18:20
【摘要】：本文针对煤矿安全隐患排查治理工作的实际需要，围绕企业隐患治理能力及其排查隐患的数量等展开评估与预测方法的研究工作。论文研究工作主要分为三部分：第一部分借鉴软件能力成熟度模型，提出企业安全隐患治理能力成熟度概念与模型，并设计了煤炭行业的评估与预测指标体系，从横、纵两个方向评估，，横向采用专家法和自组织特征映射神经网络对比评估企业间的能力成熟度；纵向基于信息熵衡量企业自身隐患治理能力的改进程度。第二部分针对企业所排查出隐患的治理能力，提出单变量的频分多曲线拟合方法来评估企业未来可能的隐患治理能力及其发展趋势。第三部分提出渐进遗忘式在线极速学习机算法，基于第一部分构建的指标体系，研究企业安全管理中的相关因素对隐患数量的影响规律，构建基于管理指标的隐患数量预测模型。研究主要选择煤炭行业的数据作为评估与预测对象，并验证本文所研究方法的有效性、适用性。
[Abstract]:In view of the actual needs of the investigation and treatment of coal mine safety hidden dangers, this paper focuses on the evaluation and prediction methods of enterprises' hidden trouble management ability and the quantity of hidden trouble investigation and so on. The research work of this paper is divided into three parts: the first part uses the software capability maturity model for reference, puts forward the concept and model of enterprise security hidden danger management capability maturity, and designs the evaluation and prediction index system of coal industry. The capability maturity of enterprises is evaluated by using expert method and self-organizing feature mapping neural network, and the degree of improvement of hidden trouble management ability is measured based on information entropy. In the second part, aiming at the management ability of hidden trouble, a single variable frequency division multi-curve fitting method is put forward to evaluate the potential hidden trouble management ability and its development trend in the future. The third part puts forward the algorithm of gradual forgetting online extreme speed learning machine. Based on the index system constructed in the first part, the paper studies the influence of related factors in enterprise safety management on the number of hidden dangers. The prediction model of hidden danger quantity based on management index is constructed. The research mainly selects the data of coal industry as the evaluation and prediction object, and verifies the validity and applicability of the method studied in this paper.
【学位授予单位】：中国矿业大学（北京）
【学位级别】：博士
【学位授予年份】：2013
【分类号】：X936
本文编号：2267136
[Abstract]:In view of the actual needs of the investigation and treatment of coal mine safety hidden dangers, this paper focuses on the evaluation and prediction methods of enterprises' hidden trouble management ability and the quantity of hidden trouble investigation and so on. The research work of this paper is divided into three parts: the first part uses the software capability maturity model for reference, puts forward the concept and model of enterprise security hidden danger management capability maturity, and designs the evaluation and prediction index system of coal industry. The capability maturity of enterprises is evaluated by using expert method and self-organizing feature mapping neural network, and the degree of improvement of hidden trouble management ability is measured based on information entropy. In the second part, aiming at the management ability of hidden trouble, a single variable frequency division multi-curve fitting method is put forward to evaluate the potential hidden trouble management ability and its development trend in the future. The third part puts forward the algorithm of gradual forgetting online extreme speed learning machine. Based on the index system constructed in the first part, the paper studies the influence of related factors in enterprise safety management on the number of hidden dangers. The prediction model of hidden danger quantity based on management index is constructed. The research mainly selects the data of coal industry as the evaluation and prediction object, and verifies the validity and applicability of the method studied in this paper.
【学位授予单位】：中国矿业大学（北京）
【学位级别】：博士
【学位授予年份】：2013
【分类号】：X936
【引证文献】
相关期刊论文 前1条
1 张瑞新;王群;王欣艳;;基于组合赋权法的隐患排查治理能力体系评价研究[J];煤炭技术;2014年05期
本文编号：2267136
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