矿井通风阻力系数随机森林反演法研究

现代矿业 ›› 2020, Vol. 36 ›› Issue (05): 205-207.

矿井通风阻力系数随机森林反演法研究

李胜男^1,2 高科^1,2 刘玉姣^1,2 周慧¹刘泽毅^1,2

1.辽宁工程技术大学安全科学与工程学院；2.矿山热动力灾害与防治教育部重点实验室

出版日期:2020-05-26 发布日期:2021-09-17

Random Forest Inversion Method for Mine Ventilation Resistance Coefficient

Li Shengnan^1,2 Gao Ke^1,2 Liu Yujiao^1,2 Zhou Hui¹Liu Zeyi^1,2

1.College of Safety Science and Engineering,Liaoning Technical University；2.Key Laboratory of Mine Thermomotive Disaster and Prevention,Ministry of Education

Online:2020-05-26 Published:2021-09-17

摘要/Abstract

摘要： 为实现矿井通风阻力系数的“少测”甚至“不测”，提高矿井通风系统仿真的准确性，研究建立了基于随机森林的矿井通风阻力系数反演方法。选取主要影响巷道通风阻力系数的巷道断面积、巷道周界及支护形式等相关的11项指标，作为随机森林矿井通风阻力系数的反演指标；通过对115条实测巷道参数进行训练学习，并用5条巷道作为验证样本进行验证；验证结果与实测结果基本相符。说明基于随机森林算法的矿井通风阻力系数反演有较好的正确性和稳定性。

关键词: 矿井通风随机森林通风阻力系数反演

Abstract: In order to achieve "less measurement" or even "exception" of the mine ventilation resistance coefficient,and to improve the accuracy of the mine ventilation system simulation,a method for inversion of the mine ventilation resistance coefficient based on random forests was established.Eleven indexes related to the cross section of the roadway,the roadway perimeter and the support form that mainly affect the roadway ventilation resistance coefficient are selected as the inversion indexes of the ventilation resistance coefficient of the random forest mine.Through training and learning of 115 measured roadway parameters,and using 5 roadways as verification samples,the verification results are basically consistent with the measured results.It shows that the mine ventilation resistance coefficient inversion based on random forest algorithm has better accuracy and stability.

Key words: Mine ventilation,Random forest,Ventilation resistance coefficient,Inversion

李胜男, 高科, 刘玉姣, 周慧刘泽毅. 矿井通风阻力系数随机森林反演法研究[J]. 现代矿业, 2020, 36(05): 205-207.

Li Shengnan, Gao Ke, Liu Yujiao, Zhou Hui Liu Zeyi. Random Forest Inversion Method for Mine Ventilation Resistance Coefficient[J]. Modern Mining, 2020, 36(05): 205-207.