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An Extended ORESTE Approach for Evaluating Rockburst Risk under Uncertain Environments

Author

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  • Keyou Shi

    (School of Resource Environment and Safety Engineering, University of South China, Hengyang 421001, China)

  • Yong Liu

    (College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518000, China)

  • Weizhang Liang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

Abstract

Rockburst is a severe geological disaster accompanied with the violent ejection of rock debris, which greatly threatens the safety of underground workers and equipment. This study aims to propose a novel multi-criteria decision-making (MCDM) approach for evaluating rockburst risk under uncertain environments. First, considering the heterogeneity of rock mass and complexity of geological environments, trapezoidal fuzzy numbers (TrFNs) are adopted to express initial indicator information. Thereafter, the superiority linguistic ratings of experts and a modified entropy weights model with TrFNs are used to calculate the subjective and objective weights, respectively. Then, comprehensive weights can be determined by integrating subjective and objective weights based on game theory. After that, the organísation, rangement et synthèse de données relarionnelles (ORESTE) approach is extended to obtain evaluation results in a trapezoidal fuzzy circumstance. Finally, the proposed approach is applied to assess rockburst risk in the Kaiyang phosphate mine. In addition, the evaluation results are compared with empirical methods and other trapezoidal fuzzy MCDM approaches. Results show that the proposed extended ORESTE approach is reliable for evaluating rockburst risk, and provides an effective reference for the design of prevention techniques.

Suggested Citation

  • Keyou Shi & Yong Liu & Weizhang Liang, 2022. "An Extended ORESTE Approach for Evaluating Rockburst Risk under Uncertain Environments," Mathematics, MDPI, vol. 10(10), pages 1-20, May.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:10:p:1699-:d:816526
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    References listed on IDEAS

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    1. Weizhang Liang & Bing Dai & Guoyan Zhao & Hao Wu, 2019. "Assessing the Performance of Green Mines via a Hesitant Fuzzy ORESTE–QUALIFLEX Method," Mathematics, MDPI, vol. 7(9), pages 1-19, August.
    2. Diyuan Li & Zida Liu & Danial Jahed Armaghani & Peng Xiao & Jian Zhou, 2022. "Novel Ensemble Tree Solution for Rockburst Prediction Using Deep Forest," Mathematics, MDPI, vol. 10(5), pages 1-23, March.
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    5. Saleem H. Ali & Damien Giurco & Nicholas Arndt & Edmund Nickless & Graham Brown & Alecos Demetriades & Ray Durrheim & Maria Amélia Enriquez & Judith Kinnaird & Anna Littleboy & Lawrence D. Meinert & R, 2017. "Mineral supply for sustainable development requires resource governance," Nature, Nature, vol. 543(7645), pages 367-372, March.
    6. Esra AYTAC ADALI & Aysegul TUS ISIK, 2017. "Ranking Web Design Firms with the ORESTE Method," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 17(2), pages 243-254.
    7. Ivan Pribićević & Suzana Doljanica & Oliver Momčilović & Dillip Kumar Das & Dragan Pamučar & Željko Stević, 2020. "Novel Extension of DEMATEL Method by Trapezoidal Fuzzy Numbers and D Numbers for Management of Decision-Making Processes," Mathematics, MDPI, vol. 8(5), pages 1-16, May.
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    9. Weizhang Liang & Asli Sari & Guoyan Zhao & Stephen D. McKinnon & Hao Wu, 2020. "Short-term rockburst risk prediction using ensemble learning methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(2), pages 1923-1946, November.
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    2. Hua Shi & Ling-Xiang Mao & Ke Li & Xiang-Hu Wang & Hu-Chen Liu, 2022. "Engineering Characteristics Prioritization in Quality Function Deployment Using an Improved ORESTE Method with Double Hierarchy Hesitant Linguistic Information," Sustainability, MDPI, vol. 14(15), pages 1-19, August.

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