[1]叶桢妮,侯恩科,段中会,等.郭家河煤矿回采工作面瓦斯涌出量预测[J].西安科技大学学报,2017,(01):57-62.[doi:10.13800/j.cnki.xakjdxxb.2017.0110]
 YE Zhen-ni,HOU En-ke,DUAN Zhong-hui,et al.Prediction for gas emission quantity of the working face in Guojiahe coal mine[J].Journal of Xi'an University of Science and Technology,2017,(01):57-62.[doi:10.13800/j.cnki.xakjdxxb.2017.0110]
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郭家河煤矿回采工作面瓦斯涌出量预测(/HTML)
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西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

卷:
期数:
2017年01期
页码:
57-62
栏目:
出版日期:
2017-01-30

文章信息/Info

Title:
Prediction for gas emission quantity of the working face in Guojiahe coal mine
文章编号:
1672-9315(2017)01-0057-06
作者:
叶桢妮1侯恩科1段中会23贺 丹24潘 怡1
1.西安科技大学 地质与环境学院,陕西 西安 710054; 2.国土资源部 煤炭资源勘查与综合利用重点实验室,陕西 西安 710026; 3.陕西省煤田地质集团有限公司,陕西 西安 710026; 4.陕西煤田地质勘查研究院有限公司,陕西 西安 710026
Author(s):
YE Zhen-ni1HOU En-ke1DUAN Zhong-hui23HE Dan24PAN Yi1
1.College of Geology and Environment,Xi'an University of Science and Technology,Xi'an 710054,China; 2.Key Laboratory of Coal Resources Exploration and Comprehensive Utilization,MLR, Xi'an 710026,China; 3.Shaanxi Coal Geology Group Co.,Ltd.,Xi'an 710026,China; 4.Shaanxi Coal Geology Bureau Investigation Research Institute, Xi'an 710026,China
关键词:
瓦斯涌出量 影响因素 多元逐步回归分析法 郭家河煤矿
Keywords:
Key words:gas emission quantity influencing factors multiple stepwise regression analysis Guojiahe coal mine
分类号:
TE 12
DOI:
10.13800/j.cnki.xakjdxxb.2017.0110
文献标志码:
A
摘要:
矿井瓦斯涌出量的准确预测,可为煤矿安全生产提供有力保障。文中以郭家河煤矿为例,通过探讨瓦斯涌出量与影响因素之间的关系,采用多元回归分析法,结合回采工作面瓦斯涌出量的实测数据和相关参数,利用“统计产品与服务解决方案软件”(简称SPSS)对影响瓦斯涌出量的因素进行多元逐步回归分析,在解决各影响因素间多重共线性问题后,建立了瓦斯涌出量预测模型。将瓦斯涌出量实测值分别与多元逐步回归法和多元线性回归法所得的预测值进行比对分析,结果表明多元逐步回归法预测结果精度更高,更适合于回采工作面瓦斯涌出量预测。
Abstract:
Abstract:In order to guarantee safety of coal mine production,it is necessary to predict the gas emission quantity.Taking Guojiahe coal mine for example,this paper based on discussion of the relationship between gas emission quantity and influencing factors.Combined with measured data of the gas and relative parameters,it has established a multivariate regression equation using the method of multiple stepwise regression analysis which overcome collinearity problem by means of the statistical products and service solutions(SPSS)software.Comparing measured values to experimental values in multiple stepwise regression model and multiple linear regression model respectively,results show that multiple stepwise regression model is more accurate and practical to gas emission forecast.

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备注/Memo

备注/Memo:
基金项目:国家自然科学基金(41502160) 通讯作者:叶桢妮(1988-),女,宁夏银川人,博士生,E-mail:yezhenni727@126.com
更新日期/Last Update: 1900-01-01