{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T22:57:23Z","timestamp":1772837843873,"version":"3.50.1"},"reference-count":30,"publisher":"World Scientific Pub Co Pte Ltd","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:p> The underground utility tunnels accommodate various types of urban lifelines, which are of great significance for improving the living standards of the citizens. With the rapid development of underground utility tunnels, the large-scale underground utility tunnel systems are gradually becoming the operational lifeblood of China\u2019s large cities. Currently, most of the underground utility tunnels\u2019 risks are estimated and analyzed from a static perspective, and the analysis results are one-sided. This study proposes a dynamic risk evaluation framework. A risk assessment and sensitivity analysis framework based on Bayesian network is established in this study. Combined with the groundwater and electric tunnel risk accident case study, the operation and maintenance data of Beijing Future Science and Technology City from 2010 to 2018 are collected for learning to obtain the conditional probability of the Bayesian network node by using the K2 algorithm. The overall evolution process from the beginning to the end of groundwater tunnel accidents is clearly described and displayed. Through sensitivity analysis and critical path analysis, the critical points of an accident and the probabilities of risk occurrence are identified and predicted. This proposed framework could facilitate the underground utility tunnel management for controlling risk resources, mitigating risk damage and reducing risk losses. <\/jats:p>","DOI":"10.1142\/s0218126623500962","type":"journal-article","created":{"date-parts":[[2022,9,25]],"date-time":"2022-09-25T14:11:06Z","timestamp":1664115066000},"source":"Crossref","is-referenced-by-count":5,"title":["Risk Assessment and Prediction of Underground Utility Tunnels Based on Bayesian Network: A Case Study in Beijing, China"],"prefix":"10.1142","volume":"32","author":[{"given":"Yongjun","family":"Chen","sequence":"first","affiliation":[{"name":"School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojian","family":"Li","sequence":"additional","affiliation":[{"name":"School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9500-2505","authenticated-orcid":false,"given":"Wenjuan","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Business Administration, Capital University of Economics and Business, 121 Zhangjialukou, Fengtai, Beijing 10070, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangye","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lulin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2022,11,14]]},"reference":[{"key":"S0218126623500962BIB001","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.tust.2015.11.012","volume":"55","author":"Broere W.","year":"2016","journal-title":"Tunn. 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