IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i15p12018-d1210928.html
   My bibliography  Save this article

Prioritization of Hazardous Zones Using an Advanced Risk Management Model Combining the Analytic Hierarchy Process and Fuzzy Set Theory

Author

Listed:
  • Kibeom Kwon

    (School of Civil, Environmental and Architectural Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Minkyu Kang

    (School of Civil, Environmental and Architectural Engineering, Korea University, Seoul 02841, Republic of Korea)

  • Dongku Kim

    (Department of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology (KICT), Goyang 10223, Republic of Korea)

  • Hangseok Choi

    (School of Civil, Environmental and Architectural Engineering, Korea University, Seoul 02841, Republic of Korea)

Abstract

Risk management plays a vital role in ensuring the safety and efficiency of tunnel construction by considering various factors, including uncertainties associated with concurrent adverse sources. One key aspect of risk management is prioritizing hazardous zones to devise an optimal countermeasure plan within time and cost constraints. This study developed an advanced tunnel risk management model, combining the analytic hierarchy process (AHP) and fuzzy set theory (FST). The model derived the impact using AHP and the probability using FST. By selectively combining causal factors that met the selection criterion, the risk of each hazardous zone was determined, enabling the prioritization of identified hazardous zones. The model application results indicated that causal combinations associated with significant tunnel convergence posed a relatively high risk. Moreover, the hazardous zones where unstable ground formations were excavated by a gripper tunnel boring machine (TBM) were revealed as the most vulnerable locations. Consequently, adopting a shield TBM or implementing ground reinforcement is recommended. Overall, the developed model effectively prioritizes identified hazardous zones and provides an optimal countermeasure plan, contributing to the overall safety and efficiency of the operations.

Suggested Citation

  • Kibeom Kwon & Minkyu Kang & Dongku Kim & Hangseok Choi, 2023. "Prioritization of Hazardous Zones Using an Advanced Risk Management Model Combining the Analytic Hierarchy Process and Fuzzy Set Theory," Sustainability, MDPI, vol. 15(15), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:12018-:d:1210928
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/15/12018/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/15/12018/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hamid Pourghasemi & Biswajeet Pradhan & Candan Gokceoglu, 2012. "Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran," 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. 63(2), pages 965-996, September.
    2. Heeyoung Chung & Jeongjun Park & Byung-Kyu Kim & Kibeom Kwon & In-Mo Lee & Hangseok Choi, 2021. "A Causal Network-Based Risk Matrix Model Applicable to Shield TBM Tunneling Projects," Sustainability, MDPI, vol. 13(9), pages 1-23, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Txomin Bornaetxea & Juan Remondo & Jaime Bonachea & Pablo Valenzuela, 2023. "Exploring available landslide inventories for susceptibility analysis in Gipuzkoa province (Spain)," 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. 118(3), pages 2513-2542, September.
    2. Gökhan Demir & Mustafa Aytekin & Aykut Akgün & Sabriye İkizler & Orhan Tatar, 2013. "A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process 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. 65(3), pages 1481-1506, February.
    3. Rui Yuan & Jing Chen, 2022. "A hybrid deep learning method for landslide susceptibility analysis with the application of InSAR data," 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. 114(2), pages 1393-1426, November.
    4. Viet-Ha Nhu & Ataollah Shirzadi & Himan Shahabi & Sushant K. Singh & Nadhir Al-Ansari & John J. Clague & Abolfazl Jaafari & Wei Chen & Shaghayegh Miraki & Jie Dou & Chinh Luu & Krzysztof Górski & Binh, 2020. "Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms," IJERPH, MDPI, vol. 17(8), pages 1-30, April.
    5. Sadhan Malik & Subodh Chandra Pal & Biswajit Das & Rabin Chakrabortty, 2020. "Assessment of vegetation status of Sali River basin, a tributary of Damodar River in Bankura District, West Bengal, using satellite data," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5651-5685, August.
    6. Nzotcha, Urbain & Kenfack, Joseph & Blanche Manjia, Marceline, 2019. "Integrated multi-criteria decision making methodology for pumped hydro-energy storage plant site selection from a sustainable development perspective with an application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 930-947.
    7. Majid Mohammady & Hamid Reza Pourghasemi & Mojtaba Amiri, 2019. "Assessment of land subsidence susceptibility in Semnan plain (Iran): a comparison of support vector machine and weights of evidence data mining algorithms," 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. 99(2), pages 951-971, November.
    8. Viet-Tien Nguyen & Trong Hien Tran & Ngoc Anh Ha & Van Liem Ngo & Al-Ansari Nadhir & Van Phong Tran & Huu Duy Nguyen & Malek M. A. & Ata Amini & Indra Prakash & Lanh Si Ho & Binh Thai Pham, 2019. "GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam," Sustainability, MDPI, vol. 11(24), pages 1-24, December.
    9. Neshat, Aminreza & Pradhan, Biswajeet & Dadras, Mohsen, 2014. "Groundwater vulnerability assessment using an improved DRASTIC method in GIS," Resources, Conservation & Recycling, Elsevier, vol. 86(C), pages 74-86.
    10. Netra Bhandary & Ranjan Dahal & Manita Timilsina & Ryuichi Yatabe, 2013. "Rainfall event-based landslide susceptibility zonation mapping," 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. 69(1), pages 365-388, October.
    11. Wenqun Xiu & Shuying Wang & Wenguang Qi & Xue Li & Chisheng Wang, 2021. "Disaster Chain Analysis of Landfill Landslide: Scenario Simulation and Chain-Cutting Modeling," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
    12. Di Wang & Mengmeng Hao & Shuai Chen & Ze Meng & Dong Jiang & Fangyu Ding, 2021. "Assessment of landslide susceptibility and risk factors in China," 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. 108(3), pages 3045-3059, September.
    13. Rajesh Khatakho & Dipendra Gautam & Komal Raj Aryal & Vishnu Prasad Pandey & Rajesh Rupakhety & Suraj Lamichhane & Yi-Chung Liu & Khameis Abdouli & Rocky Talchabhadel & Bhesh Raj Thapa & Rabindra Adhi, 2021. "Multi-Hazard Risk Assessment of Kathmandu Valley, Nepal," Sustainability, MDPI, vol. 13(10), pages 1-27, May.
    14. Aihua Wei & Duo Li & Yahong Zhou & Qinghai Deng & Liangdong Yan, 2021. "A novel combination approach for karst collapse susceptibility assessment using the analytic hierarchy process, catastrophe, and entropy model," 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. 105(1), pages 405-430, January.
    15. Amin Salehpour Jam & Jamal Mosaffaie & Faramarz Sarfaraz & Samad Shadfar & Rouhangiz Akhtari, 2021. "GIS-based landslide susceptibility mapping using hybrid MCDM models," 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. 108(1), pages 1025-1046, August.
    16. Abdessamed Derdour & Abderrazak Bouanani & Noureddine Kaid & Kanit Mukdasai & A. M. Algelany & Hijaz Ahmad & Younes Menni & Houari Ameur, 2022. "Groundwater Potentiality Assessment of Ain Sefra Region in Upper Wadi Namous Basin, Algeria Using Integrated Geospatial Approaches," Sustainability, MDPI, vol. 14(8), pages 1-20, April.
    17. Faisal AlShareef & Mohammed Aljoufie, 2020. "Identification of the Proper Criteria Set for Neighborhood Walkability Using the Fuzzy Analytic Hierarchy Process Model: A Case Study in Jeddah, Saudi Arabia," Sustainability, MDPI, vol. 12(21), pages 1-18, November.
    18. Idris Bello Yamusa & Mohd Suhaili Ismail & Abdulwaheed Tella, 2022. "Highway Proneness Appraisal to Landslides along Taiping to Ipoh Segment Malaysia, Using MCDM and GIS Techniques," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    19. Sarbast Moslem & Muhammet Gul & Danish Farooq & Erkan Celik & Omid Ghorbanzadeh & Thomas Blaschke, 2020. "An Integrated Approach of Best-Worst Method (BWM) and Triangular Fuzzy Sets for Evaluating Driver Behavior Factors Related to Road Safety," Mathematics, MDPI, vol. 8(3), pages 1-20, March.
    20. Soyoung Park & Se-Yeong Hamm & Jinsoo Kim, 2019. "Performance Evaluation of the GIS-Based Data-Mining Techniques Decision Tree, Random Forest, and Rotation Forest for Landslide Susceptibility Modeling," Sustainability, MDPI, vol. 11(20), pages 1-20, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:12018-:d:1210928. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.