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首页> 外文期刊>International Journal of Rock Mechanics and Mining Sciences >Analysis of the coal mine roof fall rate using fuzzy reasoning techniques
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Analysis of the coal mine roof fall rate using fuzzy reasoning techniques

机译：基于模糊推理技术的煤矿顶板冒落率分析

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It is the author's opinion that there is no doubt that the condition of a mine roof can be better expressed using linguistic terminologies rather than numerical values. Numerical representation of a roof condition may mean something to an engineer or a scientist who is actively involved in ground control research or in the application of roof classification techniques. For a layman or a field engineer, s/he is more interested to know whether roof fall rate at a particular drivage is "Low", or "High" or "Medium". By the same token, CMRR and PRSUP or any other parameter should also be represented using linguistic terminologies which are more accepted in the field. Fuzzy set theory and fuzzy logic provide a strong mathematical and analytical foundation for the analysis of vagueness in data which are represented by "Low", "High", "Medium", etc. In this paper, an outline is given for the analysis of roof fall rate using three parameters which are represented using five linguistics hedges. This paper also shows that fuzzy reasoning techniques can be used for the analysis of roof fall rate and may provide better understanding of the relation between input parameters to the output variable. For this purpose, nine fuzzy rules are developed based on the different the input fuzzy sets of CMRR, PRSUP and IDS and the output fuzzy set of RFR. These rules are used to form the final fuzzy relational matrix using Mamdani's principles. A computer program is developed to construct a fuzzy relational matrix from fuzzy rules and analyze RFR based on different premises or roof conditions. Four different mine roof conditions are analyzed using the final fuzzy relational matrix developed from the fuzzy rules. Out of these four roof conditions, two conditions are exactly the same as two fuzzy rules. It is found that under these circumstances, accurate forecasting of RFR is possible using fuzzy reasoning techniques. The other two roof conditions are different and cannot be matched with any fuzzy rules. In these two cases, forecasting of RFR is also possible and is provided with reasonable accuracy. However, more fuzzy rules have to be incorporated to obtain more accurate results. It is also possible to have contradictory rules when a large number of fuzzy rules is incorporated in the analysis. Fuzzy set theory can also analyze such rules in an effective manner, although there should not be contradictions between the rules.
机译：作者认为，毫无疑问，使用语言术语而不是数值可以更好地表达矿井顶的状况。对积极参与地面控制研究或屋顶分类技术应用的工程师或科学家而言，屋顶状况的数字表示可能意味着某些意义。对于外行或现场工程师来说，他/她对了解特定驾驶情况下的车顶下降率是“低”，“高”还是“中”更感兴趣。同样，CMRR和PRSUP或任何其他参数也应使用语言术语表示，该术语在本领域中更受欢迎。模糊集理论和模糊逻辑为以“低”，“高”，“中”等表示的数据中的模糊性提供了强大的数学和分析基础。使用三个参数的屋顶下降率，这三个参数用五个语言学树篱表示。本文还表明，模糊推理技术可以用于分析屋顶跌落率，并且可以更好地理解输入参数与输出变量之间的关系。为此，根据CMRR，PRSUP和IDS的输入模糊集和RFR的输出模糊集，开发了九种模糊规则。这些规则用于使用Mamdani原理形成最终的模糊关系矩阵。开发了计算机程序以根据模糊规则构建模糊关系矩阵，并根据不同的前提或屋顶条件分析RFR。使用从模糊规则得出的最终模糊关系矩阵分析了四个不同的矿顶条件。在这四个屋顶条件中，两个条件与两个模糊规则完全相同。发现在这种情况下，使用模糊推理技术可以准确地预测RFR。其他两个屋顶条件是不同的，无法与任何模糊规则匹配。在这两种情况下，RFR的预测也是可能的，并且具有合理的准确性。但是，必须合并更多的模糊规则以获得更准确的结果。当分析中包含大量模糊规则时，也可能有矛盾的规则。模糊集理论也可以有效地分析此类规则，尽管规则之间不应存在矛盾。

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