预测冲击地压危险性等级R型因子Fisher判别

doi:10.16265/j.cnki.issn1003-3033.2019.12.017

中国安全科学学报 ›› 2019, Vol. 29 ›› Issue (12): 103-109.doi: 10.16265/j.cnki.issn1003-3033.2019.12.017

预测冲击地压危险性等级R型因子Fisher判别

毕娟^1,2,3, 李希建^1,2,3 教授, 陈刘瑜^1,2,3

1 贵州大学矿业学院,贵州贵阳 550025;
2 复杂地质矿山开采安全技术工程中心,贵州贵阳 550025;
3 贵州大学瓦斯灾害防治与煤层气开发研究所,贵州贵阳 550025

收稿日期:2019-09-13 修回日期:2019-11-22 出版日期:2019-12-28 发布日期:2020-11-24
作者简介:毕娟 (1995—),女,贵州安顺人,硕士研究生,主要研究方向为矿山通风技术等。E-mail:bijuanyouxiang@163.com。
基金资助:
国家自然科学基金面上项目资助(51874107);贵州省科技计划项目(黔科合平台人才[2018]5781号)。

R-factor Fisher discrimination for rock burst hazard level prediction

BI Juan^1,2,3, LI Xijian^1,2,3, CHEN Liuyu^1,2,3

1 Mining College, Guizhou University, Guiyang Guizhou 550025, China;
2 Engineering Center for Safe Mining Technology Under Complex Geologic Condition, Guiyang Guizhou 550025, China;
3 Institute of Gas Disaster Prevention and Coalbed Methane Development, Guizhou University, Guiyang Guizhou 550025, China

Received:2019-09-13 Revised:2019-11-22 Online:2019-12-28 Published:2020-11-24

摘要/Abstract

摘要： 为提高小样本预测冲击地压危险性等级精度,提出一种R型因子分析Fisher判别的预测模型。以砚石台煤矿为例,利用R型因子分析处理冲击地压危险性评价指标,提取原有指标特征信息,用少量主因子代替原有评价指标,定性分析冲击地压危险性等级;采用Fisher判别法分析 R型因子分析处理结果,确定评价集与不同危险等级冲击地压的距离,并回判训练集,提高判断矩阵精确度;再根据判断矩阵预测冲击地压危险性等级。结果表明:该模型可弱化指标间的相互影响,明显提高小样本预测准确度。

关键词: 冲击地压, R型因子分析, 降维分析, Fisher判别法, 预测模型, 危险性评价

Abstract: In order to improve prediction accuracy of hazard levels of rock burst with a small sample, an R-type factor analysis-Fisher discriminant prediction model is proposed. Firstly, with Yanshitai Coal Mine as an example, R-type factor analysis was used to process risk assessment index of rock burst, characteristic information of original index was extracted which were then replaced by a small number of main factors, and qualitative analysis of hazard levels was performed. Secondly, Fisher discriminant method was adopted to analyze R-type factor analysis results to determine distance between assessment set and different risk levels, and accuracy of judgment matrix was improved by rejudging training set. Finally, risk levels of rock burst were predicted according to judgment matrix. The results show that this model can weaken interaction between indicators and significantly improve predication accuracy for small samples.

Key words: rock burst, R-factor analysis, dimensionality analysis, Fisher discriminant method, prediction model, hazard assessment

中图分类号:

X936

毕娟, 李希建, 陈刘瑜. 预测冲击地压危险性等级R型因子Fisher判别[J]. 中国安全科学学报, 2019, 29(12): 103-109.

BI Juan, LI Xijian, CHEN Liuyu. R-factor Fisher discrimination for rock burst hazard level prediction[J]. China Safety Science Journal, 2019, 29(12): 103-109.

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预测冲击地压危险性等级R型因子Fisher判别

R-factor Fisher discrimination for rock burst hazard level prediction

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