[an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive]
[an error occurred while processing this directive]

Gold Science and Technology >

2022 , Vol. 30 >Issue 5: 704 - 712

DOI: https://doi.org/10.11872/j.issn.1005-2518.2022.05.148

Mining Technology and Mine Management

Rock Mass Quality Evaluation and Application Based on Game Theory and G1-EW-TOPSIS Method

  • Xianfeng XU ,
  • Pengfei XING ,
  • Suihong WANG ,
  • Yong WANG
Expand
  • Nuclear Industry Jingxiang Construction Group Co. ，Ltd. ，Huzhou 303002，Zhejiang，China

Received date: 2021-10-12

  Revised date: 2022-06-08

  Online published: 2022-12-10

Fold

Highlights

The reasonable evaluation of rock quality is the basis for engineering design and construction，and it is of great significance to the safe production and economic benefits of mines.In view of the complex conditions and ambiguity of rock quality evaluation，on the basis of comprehensive reference to relevant research literature，five parameters were selected as rock quality evaluation indexes，including core quality index RQD value（X 1），uniaxial compressive strength of rock σ c（X 2），rock integrity coefficient K v（X 3），structural surface strength coefficient J（X 4）and unit time water seepage S（X 5），and a rock quality evaluation model of G1-EW-TOPSIS method based on game theory idea was proposed and applied to the rock quality evaluation of the first mining middle section of a silver polymetallic mine in Inner Mongolia.To verify the validity of the model，firstly，a field survey was conducted to determine five measurement points for the structural surface condition and groundwater flow of the rock mass in the first mining middle section of the mine，and then the subjective weight ω 1 and objective weight ω 2 of the indexes of the measurement points were obtained by combining the G1 method and EW method through game theory to obtain the comprehensive weight ω .Finally，TOPSIS was used to calculate the relative closeness of each measurement point under each rock quality class to determine the rock quality class of the measurement point.The results show that the five rock quality grade evaluation indexes selected in this paper can better reflect the state of the rock mass.The method of calculating the com-prehensive weight of the model not only overcomes the shortcomings of the single assignment method，but also reduces the error and improves the ability of the model to deal with multi-objective decision problems.The rock quality in the first middle section of this mine is mainly evaluated as grade Ⅲ and grade Ⅳ，the rock quality is poor，and the support needs to be strengthened for the roadway and the exposed surrounding rock of the quarry where the rock quality is grade Ⅳ.The calculation results of the model completely match with the rock quality of 5 measurement points at the mine engineering site，which provides a new idea for rock quality evaluation.

Cite this article

Xianfeng XU , Pengfei XING , Suihong WANG , Yong WANG . Rock Mass Quality Evaluation and Application Based on Game Theory and G1-EW-TOPSIS Method[J]. Gold Science and Technology, 2022 , 30(5) : 704 -712 . DOI: 10.11872/j.issn.1005-2518.2022.05.148

[an error occurred while processing this directive]

据悉，山东黄金地质研究院将围绕地质勘查及资源开发利用等领域难题，积极引进高端人才和先进技术，着力从地质勘查手段及新技术应用、地质资源信息化及成矿预测等方面开展科研攻关，立争孵化更多找矿理论，攻克更多关键技术，努力建设成国内行业领先的地质勘查技术研发基地和地质勘查人才培养基地，为实现新一轮找矿突破，保障国家资源安全作出更多更大贡献。

山东黄金集团有限公司）

http://www.goldsci.ac.cn/article/2022/1005-2518/1005-2518-2022-30-5-704.shtml

References

Publishing order | Descend order by publishing year | Descend order by cited within
Bridges D S，2004.First steps in constructive game theory［J］.Mathematical Logic Quarterly，（50）：501-506.

Cao Chen， Li Huizhong， Chen Jianping，et al，2017.Dam foundation rock mass quality evaluation based on combination weighting method and cloud model ［J］.Journal of Northeastern University（Natural Science），（38）：1643-1647.

Changjiang River Scientific Research Institute of Changjiang Water Resources Commission，1995. Standard for engineering classification of rock masses：GB 50218-94 ［S］.Beijing：China Planning Press.

Chen C S， Liu Y C，2006.A methodology for evaluation and classification of rock mass quality on tunnel engineering［J］.Tunnelling and Underground Space Technology Incorporating Trenchless Technology Research，22（4）：377-387.

Chen Zhiqiang， Wang Yiming， Chen Shunman，2019.Stability analysis of goaf based on entropy weight method and fuzzy Theory［J］.Mining Research and Development，39（5）：39-43.

Ding Zhenjie， Zheng Jun， Qing Lü，et al，2019.Discussion on calculation methods of quality index of slope engineering rock mass in Standard for Engineering Classification of Rock Mass［J］.Rock and Soil Mechanics，40（Supp.1）：275-280.

Gong Fengqiang， Li Xibing，2007.Application of distance discriminant analysis method in classification of rock mass quality ［J］.Chinese Journal of Rock Mechanics and Engineering，（1）：194-198.

He Yunsong， Xue Qiuchi， Zhao Qihua，2017.Improved support vector machine-based study on rock mass quality classification［J］.Water Resources and Hydropower Engineering，48（1）：133-138.

Hu Jianhua， Ai Zihua，2017.Extension evaluation model of underground mine rock mass quality based on optimal combination weighting ［J］.Gold Science and Technology，25（4）：39-45.

Hu Jianhua， Guo Mengmeng， Zhou Tan，et al，2021.Rock mass quality evaluation model based on improved transfer learning algorithm［J］.Gold Science and Technology，29（6）：826-833.

Kang Zhiqiang， Feng Xiating， Zhou Hui，2006.Application of extensics theory to evaluation of underground cavern rock quality based on stratification analysis method ［J］.Chinese Journal of Rock Mechanics and Engineering，（Supp.2）：3687-3693.

Liu Feiyue， Liu Yihan， Yang Tianhong，2021.Fine evaluation of mine rock mass quality based on core image deep learning［J］.Chinese Journal of Geotechnical Engineering，43（5）：968-974.

Liu Qiang， Li Xibing， Liang Weizhang，2018.PCA-RF model for rock mass quality classification and its application［J］.Gold Science and Technology，26（1）：49-55.

Lu Fangyuan，2003.An improved TOPSIS method ［J］.Statistics & Decision，（3）：78-79.

Qi Wei， Li Wei， Li Zhenyang，et al，2020.Rock mass quality evaluation of underground mine based on CRITIC-CW me-thod［J］.Gold Science and Technology，28（2）：264-270.

Qiu Daohong， Chen Jianping， Que Jinsheng，et al，2008.Rock mass quality evaluation of cavern based on rough set and artificial neural network ［J］.Journal of Jilin University（Earth Science Edition），38（1）：86-91.

Tang Hai， Wan Wen， Liu Jinhai，2011.Evaluation of rock mass quality in underground caverns based on unascertained measure theory ［J］.Rock and Soil Mechanics，32（4）：1181-1185.

Tang Xiaoling， Lin Min， Liu Leilei，2021.Mining scheme optimization model based on game theory combination weighting TOPSIS method and its application［J］.Mining Research and Development，41（5）：5-10.

Tu W F， Li L P， Li S C，et al，2019.Research on the application of dynamic weighting on the rock mass quality rating［J］.Arabian Journal of Geosciences，12：1-9.

Wang Xuejun， Guo Yajun， Lan Tian，2006.Rank correlation analysis of formation of consistent judgment matrix［J］.Journal of Northeastern University，（1）：115-118.

Warren S N， Kallu R R， Barnard C K，2016.Correlation of the rock mass rating（RMR） system with the unified soil classification system（USCS）：Introduction of the weak rock mass rating system（W-RMR）［J］.Rock Mechanics and Rock Engineering，49（11）：4507-4518.

Wu X M，2009.A weighted generalized maximum entropy estimator with a data-driven weight［J］.Entropy，（11）：917-930.

Zhao Guoyan， Liu Leilei， Wang Jianbo，et al，2019.PCA-OPF model for rockburst grade prediction ［J］.Mining and Metallurgical Engineering，39（4）：1-5.

Zhao Guoyan， Qiu Ju， Zhao Yuan，et al，2020.Study on the evaluation index system and combination weighting method of green mining of metal mine［J］.Journal of Safety and Environment，20（6）：2309-2316.

Zhao Guoyan， Zhu Xubo， Su Long，2012.Research on extension evaluation of rock mass quality for underground mine based on game theory［J］.Mining Research and Development， 32（1）：12-16.

Zhou Tan， Hu Jianhua， Kuang Ye，2019.Rock mass quality evaluation method and application based on fuzzy RES-multidimensional cloud model［J］.The Chinese Journal of Nonferrous Metals，29（8）：1771-1780.

曹琛，李会中，陈剑平，等，2017.基于组合赋权法与云模型坝基岩体质量评价［J］.东北大学学报（自然科学版），（38）：1643-1647.

长江水利委员会长江科学院，1995. 工程岩体分级标准：GB 50218-94 ［S］.北京：中国计划出版社.

陈志强，王贻明，陈顺满，2019.基于熵权法和模糊理论的采空区稳定性分析［J］.矿业研究与开发，39（5）：39-43.

丁振杰，郑俊，吕庆，等，2019.《工程岩体分级标准》中边坡工程岩体质量指标计算方法的讨论［J］.岩土力学，40（增1）：275-280.

宫凤强，李夕兵，2007.距离判别分析法在岩体质量等级分类中的应用［J］.岩石力学与工程学报，（1）：194-198.

何云松，薛秋池，赵其华，2017.基于改进向量机的岩体质量分级研究［J］.水利水电技术，48（1）：133-138.

胡建华，艾自华，2017.基于最优组合赋权的地下矿山岩体质量可拓评价模型［J］.黄金科学技术，25（4）：39-45.

胡建华，郭萌萌，周坦，等，2021.基于改进迁移学习算法的岩体质量评价模型［J］.黄金科学技术，29（6）：826-833.

康志强，冯夏庭，周辉，2006.基于层次分析法的可拓学理论在地下洞室岩体质量评价中的应用［J］.岩石力学与工程学报，（增2）：3687-3693.

刘飞跃，刘一汉，杨天鸿，2021.基于岩芯图像深度学习的矿山岩体质量精细化评价［J］.岩土工程学报，43（5）：968-974.

刘强，李夕兵，梁伟章，2018.岩体质量分类的PCA-RF模型及应用［J］.黄金科学技术，26（1）：49-55.

卢方元，2003.一种改进的TOPSIS法［J］.统计与决策，（3）：78-79.

戚伟，李威，李振阳，等，2020.基于CRITIC-CW法的地下矿岩体质量评价［J］.黄金科学技术，28（2）：264-270.

邱道宏，陈剑平，阙金声，等，2008.基于粗糙集和人工神经网络的洞室岩体质量评价［J］.吉林大学学报（地球科学版），38（1）：86-91.

唐海，万文，刘金海，2011.基于未确知测度理论的地下洞室岩体质量评价［J］.岩土力学，32（4）：1181-1185.

唐晓灵，林敏，刘雷磊，2021.基于博弈论组合赋权-TOPSIS法的采矿方案优选模型及应用［J］.矿业研究与开发，41（5）：5-10.

王学军，郭亚军，兰天，2006.构造一致性判断矩阵的序关系分析法［J］.东北大学学报，（1）：115-118.

赵国彦，刘雷磊，王剑波，等，2019.岩爆等级预测的PCA-OPF模型［J］.矿冶工程，39（4）：1-5.

赵国彦，邱菊，赵源，等，2020.金属矿绿色开采评价指标体系及组合赋权法研究［J］.安全与环境学报，20（6）：2309-2316.

赵国彦，朱旭波，苏龙，2012.基于博弈论的地下矿山岩体质量可拓评价研究［J］.矿业研究与开发，32（1）：12-16.

周坦，胡建华，匡也，2019.基于模糊RES-多维云模型的岩体质量评判方法与应用［J］.中国有色金属学报，29（8）：1771-1780.

Options
Outlines

/

〈 〉

[an error occurred while processing this directive]