Toward Intelligent Early-warning for Rockburst in Underground Engineering:An Improved Multi-criteria Group Decision-making Approach Based on Fuzzy Theory

被引：0
|
作者：
Yin X. [1 ,2 ]
Liu Q. [2 ]
Ding Z. [1 ]
Zhang Q. [2 ]
Wang X. [2 ]
Huang X. [1 ,3 ]
机构：
[1] State Key Laboratory of Coal Resources in Western China, Xi'an University of Science and Technology, Xi'an
[2] School of Civil Engineering, Wuhan University, Wuhan
[3] State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan
来源：
Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering | 2022年 / 30卷 / 02期
关键词：
CRITIC algorithm; Fuzzy theory; Intelligent construction; PROMETHEE algorithm; Rockburst proneness; Underground engineering;
D O I：
10.16058/j.issn.1005-0930.2022.10.011
中图分类号：
学科分类号：
摘要：
Rockburst is a common kind of dynamic geological disaster in underground engineering, seriously restricting the development and utilization of underground space and resources. The study on rockburst proneness prediction has important theoretical and practical significance. Considering the mechanism and characteristics of rockburst, rock brittleness index (B1), strain energy storage index (Pes), elastic strain energy index (Wet), stress concentration factor (SCF) and rock mass integrity coefficient (Kv) are selected as evaluation attributes. In view of the complexity of engineering geological conditions, and the anisotropy and heterogeneity of rock, the above attributes have the ambiguity. Only using the average value as attribute values is difficult to describe their essential characteristics. Therefore, fuzzy theory is introduced and trapezoidal fuzzy number is employed to represent the original data. An improved CRITIC algorithm is proposed for determining attribute weights in fuzzy environment. On this basis, an improved weighted PROMETHEE decision-making algorithm is raised to transform rockburst proneness prediction into a multi-attribute group decision-making problem in fuzzy environment. Finally, a improved CRITIC-PROMETHEE intelligent model based on fuzzy theory for rockburst proneness prediction is established. The model is tested by rockburst cases collected from Xincheng gold mine and then it is compared with unimproved PROMETHEE model, TOPSIS model, TODIM model and actual situation. The results indicate that the proposed model is feasible and applicable, and taking into account the ambiguity of data can effectively improve the prediction accuracy. Besides, a sensitivity analysis is conducted on the fuzzy factor (α) to discuss its influence on model performance. The CRITIC-PROMETHEE model improved by fuzzy theory provides a new and reliable method for rockburst proneness intelligent prediction. © 2022, The Editorial Board of Journal of Basic Science and Engineering. All right reserved.
引用
收藏
页码：374 / 395
页数：21
相关论文
共 37 条
  • [1] Li Pengxiang, Chen Bingrui, Zhou Yangyi, Et al., Research progress of rockburst prediction and early warning in hard rock underground engineering, Journal of China Coal Society, 44, S2, pp. 447-465, (2019)
  • [2] Jiang Feifei, Zhou Hui, Liu Chang, Et al., Progress, prediction and prevention of rockbursts in underground metal mines, Chinese Journal of Rock Mechanics and Engineering, 38, 5, pp. 956-972, (2019)
  • [3] Feng Xiating, Xiao Yaxun, Feng Guangliang, Et al., Study on the development process of rockbursts, Chinese Journal of Rock Mechanics and Engineering, 38, 4, pp. 649-673, (2019)
  • [4] Chen Weizhong, Ma Chishuai, Tian Hongming, Et al., Discussion on rockburst predictive method applying to TBM tunnel construction, Rock and Soil Mechanics, 38, pp. 241-249, (2017)
  • [5] Zhang Jingjian, Fu Bingjun, Rockburst and its criteria and control, Chinese Journal of Rock Mechanics and Engineering, 10, pp. 2034-2042, (2008)
  • [6] Barton N R., Some new Q-value correlations to assist in site characterization and tunnel design, International Journal of Rock Mechanics and Mining Sciences, 39, 2, pp. 185-216, (2002)
  • [7] KIDYBINSKI A., Bursting liability indices of coal, International Journal of Rock Mechanics and Mining Sciences, 18, 4, pp. 295-304, (1981)
  • [8] Wang Yuanhan, Li Wodong, Li Qiguang, Et al., Method of fuzzy comprehensive evaluations for rockburst prediction, Chinese Journal of Rock Mechanics and Engineering, 17, 5, pp. 493-501, (1998)
  • [9] Chen Luwang, Yin Xiaoxi, Zhao Yu, Simulation of rockburst in hard and brittle surrounding rocks of circular underground cavern, Journal of Basic Science and Engineering, 17, 6, pp. 935-942, (2009)
  • [10] Beck D A, Brady B H G., Evaluation and application of controlling parameters for seismic events in hard-rock mines, International Journal of Rock Mechanics and Mining Sciences, 39, 5, pp. 633-642, (2002)
1234