Abstract
To further enriching the safety system evaluation theory and comprehensively evaluate an control system for back-filling. This paper constructed a set pair matter-element extension comprehensive evaluation model based on the whole process theory, a multi-level comprehensive safety evaluation index system for back-filling control system. The index system was constructed by selecting 16 influencing factors from four aspects: slurry preparation system, pipeline monitoring system, strength monitoring system, and system visual management. Weights of the indicators are calculated by order relationship method, entropy weight method, and Lagrange combination weighting method. According to the set pair matter element extension calculation principle, a single indicator connection membership function is constructed. By calculating the single indicator connection membership degree and the comprehensive connection membership degree, the level of the control system for back-filling is comprehensively analyzed using the maximum membership degree as the criterion; Finally, taking three mines as examples, the blind number theory was introduced to determine the indicator assignment, and a comprehensive safety evaluation of the system level was conducted. The evaluation results were compared with cloud model and attribute recognition model. The results show that the evaluation results of the three models are consistent and consistent with the actual situation, indicating that the comprehensive evaluation model based on combination weighting method and set-pair extension matter element is applicable in the evaluation of control system for back-filling.
Similar content being viewed by others
Data availability
The datasets used or analyzed in this study are available from the corresponding author on reasonable request.
References
Yang, J. et al. On intelligent mining with parallel intelligence. IEEE Trans. Intell. Vehicles 8 (10), 1–5 (2023).
Tomasz, P. PawlakCA1, Jędrzej Potoniec2. ProcessM: intelligent process mining software. SoftwareX 30, 102079 (2025).
Qi, C. & Fourie, A. Cemented paste backfill for mineral tailings management:Review and future perspectives. Miner. Eng. 144, 106025 (2019).
Xie, H. et al. Machine learning of concrete temperature development for quality control of field curing. J. Comput. Civ. Eng. 34 (5), 04020031 (2020).
Zheng, D. et al. Delicate control of graphite flakes alignment in the copper matrices via powder selections and filling processes. Mater. Res. Express 11 (1), 016517 (2024).
Zhang, S. et al. A global optimization algorithm for intelligent electromechanical control system with improved filling function. Sci. Program. 2022, 1–10 (2022).
Tian, D. & Song, X. Design and control of an automatic high-viscosity sealant filling system. Proc. Inst. Mechan. Eng. Part I: J. Syst. Control Eng. 235 (7), 1237–1244 (2021).
Espitia-Cuchango, H., Machón-González, I. & López-García, H. Filling control of a conical tank using a compact neuro-fuzzy adaptive control system. Complexity 2022, 4284378 (2022).
Qi, C. et al. Towards intelligent mining for backfill: A genetic programming-based method for strength forecasting of cemented paste backfill. Min. Eng. 133, 69–79 (2019).
Gang, Li., Dengpan, Q. & Tianyu, Y. Intelligent regression study on paste filling mix proportion based on stacking model. Nonferr. Metals 15 (9), 1619–1630 (2025).
Xuebin, Q. et al. Research on Monitoring and early warning of the mine backfill system based on blockchain technology. Appl. Sci. 13 (1), 196 (2022).
Ai, C. et al. Study on the mechanism of erosion and wear of elbow pipes by coarse particles in filling slurry. Sci. Rep. 14 (1), 30888 (2024).
Xiangsheng, K. et al. Intelligent pressure regulation control system for high-concentration ultra-fine tailings pumping and filling. Nonferr. Metals Eng. 14 (9), 130–137 (2024).
Xinzheng, C., Xiaocong, Y., Guo Lijie, Xu. & Wenyuan, S. C. Design and engineering application of mine filling intelligent control system. Non-ferr. Metal Eng. 12 (02), 114–120 (2022).
Zengzeng, W. et al. Intelligent filling system enables the new development of mines. Min. Res. Dev. 42 (01), 156–161 (2022).
Chen, C. & Ma, B. Risk evaluation of tailings dam-break based on the extension matter-element model. E3S Web Conf. 253, 01056 (2021).
Liu, S. & Li, W. Indicators sensitivity analysis for environmental engineering geological 0patterns caused by underground coal mining with integrating variable weight theory and improved matter-element extension model. Sci. Total Environ. 686, 606–618 (2019).
Xiao, L., Wenquan, Z., Xin, W., Zaiyong, W. & Chuming, P. Evaluation on the Risk of water inrush due to roof bed separation based on improved set pair analysis-variable fuzzy sets. ACS Omega 7 (11), 9430–9442 (2022).
Zaihai, W. et al. Application of extended set pair analysis on wear risk evaluation of backfill pipeline. Sustainability 14 (23), 15535 (2022).
Yang, D., Xingang Yang, S., Lei, L. G. & Cao, B. Research on green comprehensive evaluation model of urban distribution network electric energy based on CRITIC-order relation analysis method combination weighting. E3S Web Conf. 233, 01145 (2021).
Li, Q., Luo, Z. & Zhao, G. Durability evaluation of hydraulic tunnel lining structure based on set pair analysis and extension coupling model. J. Sustain. 15 (14), 11326 (2023).
Wei, H., Ningning, S. & Xiaozhong, Li. Safety assessment of steel sheet pile cofferdams for bridge deep water foundation based on set-extension theory. Safety Environ. Eng. 30 (4), 1–8 (2023).
Wei, L. et al. Intelligent control technology for complex property filling aggregate mix proportion. Min. Technol. 25 (3), 216–220 (2025).
Jianhui, Y., Qian, K. & Shuai, R. Research and application of filling pipeline failure set based on combination weighting in a K-extension model. Metal Mining 12, 183–189 (2021).
Hongkai, C., Qingbiao, G., Liang, W. & Xiangrui, M. Evaluation of slope stability within the influence of mining based on combined weighting and finite cloud model. Energy Explorat. Exploitat. 41 (2), 636–655 (2023).
Mei, Q. et al. Multifactor prediction of the water richness of coal roof aquifers based on the combination weighting method and TOPSIS model: A case study in the Changcheng No. 1 coal mine. ACS Omega 7 (49), 44984–45003 (2022).
Bi, Q. P. et al. Screening of evaluation index and construction of evaluation index system for mine ventilation system. Sustainability (Switzerland) 13 (21), 11810 (2021).
Qingfu, L., Zhuangzhuang, L. & Guanming, Z. Durability evaluation of hydraulic tunnel lining structure based on set pair analysis and extension coupling model. J. Sustain. 15 (14), 11326 (2023).
Xiang, J., Chen, J. & Zhang, A. Multi-objective ore blending optimization for polymetallic open-pit mines based on improved matter-element extension model and NSGA-II. J. Math. 13 (11), 1843–1843 (2025).
Biyong, Z. Research on safety assessment of open pit blasting based on blind number theory and improved cloud model. Nonferrous Metals Sci. Eng. 15 (4), 543–552 (2024).
Xinsheng, C., Gaoyong, S. & Haiyun, Z. An intelligent GRA-KL-TOPSIS evaluation model for coal mine production system based on game theory. Min. Res. Dev. 44 (9), 194–203 (2024).
Xinsheng, C., Gaoyong, S. & Haiyun, Z. Research on quantitative evaluation model for maturity of filling intelligent control system. Min. Res. Dev. 44 (06), 189–197 (2024).
He, J., Li, Z., Yan, Z., Xu, M., Shang, S. & Liu, B. A risk assessment model for strategic maritime passages based on blind number theory. ICIC Express Lett. 7(10). (2013).
Xiangyu, K., Xuebin, X., Yi, Z., Qian, K. & Qi, L. Research on comprehensive evaluation model of a truck dispatching system in open-pit mine. Sustainability 14 (15), 9062 (2022).
Xiaojie, Y., Zhenli, H., Gaotong, Ma. & Gan, Li. Research on slope stability evaluation based on improved set pair analysis method: A case of tonglvshan open-pit mine. Shock Vibrat. 2021, 6713581 (2021).
Wang, Y., Shou Rong, W. & Wang, Z. H. Study of the comparison and selection method of the mining project investment based on entropy-weight method. Appl. Mechan. Mater. 1447, 94–96 (2011).
Wang, S., Yuan, C. & Li, L. Application of research on risk assessment of roadway roof falls based on combined weight matter element extension model. J. Appl. Sci. 14 (10), 4111 (2024).
Xinxin, N. & Jingjing, Z. Safety production risk rating of open pit mine based on improved element extension theory. J. Safety Environ. 19 (04), 1140–1148 (2019).
Feng, G., Wei Ya, Xu. & Fei, Xu. Optimized Based on cloud model extension assessment of slope stability. Adv. Mater. Res. 163, 2709–2714 (2010).
Wang, S. et al. Risk assessment of water inrush in tunnels based on attribute interval recognition theory. J. Central South Univ. Sci. Technol. Min. Metallur. 27 (1), 517–530 (2020).
Acknowledgements
We thank the people who participated in this study.
Funding
The present study was supported by the Natural Science Foundation of Hunan Province (2023JJ40546).
Author information
Authors and Affiliations
Contributions
All authors contributed to the study conception and design. Yu Yin: Conceptualization, Methodology, Data curation, Writing-original draft. Shijiao Yang: Conceptualization, Writing-review & editing. Yushan Yang: Methodology. Zhenpeng Guo: Resources. Jian Pan: Investigation, Methodology, Project administration, Writing-review & editing. Kaixuan Wang: Project administration, Writing-review & editing.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Consent for publication
All authors approved the final manuscript.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Yin, Y., Yang, S., Yang, Y. et al. Comprehensive safety evaluation for back-filling control system based on modified set pair matter-element extension model. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39557-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-39557-6
