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Exploring land subsidence factors with linear Diophantine multi-fuzzy soft information: a hybrid CRITIC-TOPSIS framework

Author

Listed:
  • Jeevitha Kannan

    (SRM Institute of Science and Technology)

  • Vimala Jayakumar

    (Alagappa University)

  • Muhammad Riaz

    (University of the Punjab)

  • Dragan Pamucar

    (University of Belgrade
    Dogus University
    Yuan Ze University)

  • Nithya Sri Shanmugam

    (Alagappa University)

  • Vladimir Simic

    (University of Belgrade
    Vilnius Gediminas Technical University
    Korea University)

Abstract

Land subsidence is a prevalent issue that affects populations globally. It is essential to comprehend the causes and contributing elements of land subsidence to prioritize and find appropriate mitigation strategies. This research aims to highlight the significance of prioritizing the factors contributing to land subsidence. The concept of a linear Diophantine multi-fuzzy soft set (LDMFSS) provides a three way method for handling uncertainties with membership grades, reference parameters and multiplicity to develop innovative expert systems for multi-criteria decision making (MCDM) problems. New CRITIC-TOPSIS framework is developed by combining "Technique for Order of Preference by Similarity to Ideal Solution" (TOPSIS) and the "Criteria Importance Through Intercriteria Correlation" (CRITIC) technique. The first stage of proposed integrated framework is to generate the criterion weights and second stage is to determine the ranking of feasible alternatives. A practical application of CRITIC-TOPSIS is studied for prioritizing the factors of land subsidence with linear Diophantine multi-fuzzy soft information. This is mostly due to the possible effects on the environment and infrastructure. Moreover, the feasibility and accessibility are evaluated by comparing its findings with the outcomes of the previously implemented techniques.

Suggested Citation

  • Jeevitha Kannan & Vimala Jayakumar & Muhammad Riaz & Dragan Pamucar & Nithya Sri Shanmugam & Vladimir Simic, 2025. "Exploring land subsidence factors with linear Diophantine multi-fuzzy soft information: a hybrid CRITIC-TOPSIS framework," 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. 121(15), pages 17991-18031, August.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:15:d:10.1007_s11069-025-07502-x
    DOI: 10.1007/s11069-025-07502-x
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    References listed on IDEAS

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    1. Fengkai Li & Guolin Liu & Qiuxiang Tao & Min Zhai, 2023. "Land subsidence prediction model based on its influencing factors and machine 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. 116(3), pages 3015-3041, April.
    2. Binghong Pan & Shangru Liu & Zhenjiang Xie & Yang Shao & Xiang Li & Ruicheng Ge, 2021. "Evaluating Operational Features of Three Unconventional Intersections under Heavy Traffic Based on CRITIC Method," Sustainability, MDPI, vol. 13(8), pages 1-30, April.
    3. Deng-Feng Li & Jiang-Xia Nan, 2011. "Extension of the TOPSIS for Multi-Attribute Group Decision Making under Atanassov IFS Environments," International Journal of Fuzzy System Applications (IJFSA), IGI Global Scientific Publishing, vol. 1(4), pages 47-61, October.
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