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Study on the coal mine safety assessment based on rough set - neural network - evidence theory

机译:基于粗糙集 - 神经网络的煤矿安全评估研究 - 证据理论

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The safe reliability assessment of coal mine safety system is a multifactor overall merit problem. In this paper, we firstly introduced the principle and method of coal mine safety assessment based on rough set - neural network - evidence theory. Secondly, we used rough set method to carry out the pretreatment of information. Thirdly, according to the information structure after treatment, we formed the information processing system of rough set - neural network - evidence theory. Finally, we carried out the analysis of fusion result. In conclusion, we applied rough set, neural network, D-S evidence theory to the processing of safe mass monitoring data, which can reduce the uncertainty in the process of data processing. It provides us an effective basis and method to know the security situation and the development trend, and to analyze the cause and the harm of the coal mine accident.
机译:煤矿安全系统的安全可靠性评估是一个多重吸引人的整体优点问题。本文首先介绍了基于粗糙集 - 神经网络的煤矿安全评估原理和方法 - 证据理论。其次,我们使用粗糙集方法来执行信息的预处理。第三,根据治疗后的信息结构,我们形成了粗糙集 - 神经网络的信息处理系统 - 证据理论。最后,我们进行了对融合结果的分析。总之,我们应用了粗糙集,神经网络,D-S证据理论到了安全群众监测数据的处理,这可以降低数据处理过程中的不确定性。它为我们提供了一种了解安全局势和发展趋势的有效基础和方法,并分析了煤矿事故的原因和危害。

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