 Novel model for risk identification during karst excavationSong-Shun Lin, Shui-Long Shen, Annan Zhou and Ye-Shuang Xu Reliability Engineering and System Safety, 2021, vol. 209, issue C Abstract: This study proposes a novel fuzzy model for identifying high-risk factors during excavations in urban karst geological environments. The proposed model incorporates the interval analytic hierarchy process (I-AHP) into the technique for order preference by similarity to an ideal solution (TOPSIS). The developed model considers the complex geological conditions, monitoring data, management quality, and surrounding environment. I-AHP is employed to assign the weights of the criteria, while TOPSIS is applied to identify high-risk factors. An expert confidence index is introduced to increase the reliability of the evaluated results. A case study of karst excavation at Ma'anshan Park Station on Guangzhou Metro Line 9 is analysed to validate the proposed model. The results indicate that high-risk factors can be identified in different excavation stages. The evaluated results concerning variations in risk factors can provide a guide for adopting construction measures to mitigate risk and reduce accident occurrence. Keywords: I-AHP; Fuzzy TOPSIS; Risk identification; Expert confidence index; Karst excavation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:209:y:2021:i:c:s0951832021000077 DOI: 10.1016/j.ress.2021.107435 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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