A robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian network
Abstract This paper proposes a robust method utilizing Multi-state Fuzzy Bayesian Network (MFBN) to evaluate bridge safety risks, offering a foundation for risk control. Initially, a bridge collapse fault tree and a directed acyclic graph are constructed to analyze causal relationships. Subsequently...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-15235-x |
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| _version_ | 1849226208850477056 |
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| author | Zhong Cao Weicong He Kaihong Chen Rui Rao Zhaohui Chen |
| author_facet | Zhong Cao Weicong He Kaihong Chen Rui Rao Zhaohui Chen |
| author_sort | Zhong Cao |
| collection | DOAJ |
| description | Abstract This paper proposes a robust method utilizing Multi-state Fuzzy Bayesian Network (MFBN) to evaluate bridge safety risks, offering a foundation for risk control. Initially, a bridge collapse fault tree and a directed acyclic graph are constructed to analyze causal relationships. Subsequently, bridge nodes are categorized into three states, enhancing traditional binary states. Expert judgment ability and subjective reliability levels are considered to ensure survey data reliability, using confidence indices to establish multi-state fuzzy conditional probability tables. Lastly, the improved similarity aggregation method incorporates age as a factor to aggregate expert opinions, determining safety risk probabilities of root nodes. This approach assesses bridge safety risk levels with prior knowledge and evidence, identifying critical nodes contributing to heightened risks, aiding in the formulation of risk management strategies. Application to two urban bridges demonstrates the method’s effectiveness and robustness, positioning it as a valuable decision-making tool for bridge safety risk management. |
| format | Article |
| id | doaj-art-5c8d30b551ff4b199948242dc91b3e10 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5c8d30b551ff4b199948242dc91b3e102025-08-24T11:31:06ZengNature PortfolioScientific Reports2045-23222025-08-0115112010.1038/s41598-025-15235-xA robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian networkZhong Cao0Weicong He1Kaihong Chen2Rui Rao3Zhaohui Chen4School of Electronics and Communication Engineering, Guangzhou UniversitySchool of Electronics and Communication Engineering, Guangzhou UniversitySchool of Electronics and Communication Engineering, Guangzhou UniversityResearch Center for Wind Engineering and Engineering Vibration, Guangzhou UniversitySchool of Mathematics, Physics and Data Science, Chongqing University of Science and TechnologyAbstract This paper proposes a robust method utilizing Multi-state Fuzzy Bayesian Network (MFBN) to evaluate bridge safety risks, offering a foundation for risk control. Initially, a bridge collapse fault tree and a directed acyclic graph are constructed to analyze causal relationships. Subsequently, bridge nodes are categorized into three states, enhancing traditional binary states. Expert judgment ability and subjective reliability levels are considered to ensure survey data reliability, using confidence indices to establish multi-state fuzzy conditional probability tables. Lastly, the improved similarity aggregation method incorporates age as a factor to aggregate expert opinions, determining safety risk probabilities of root nodes. This approach assesses bridge safety risk levels with prior knowledge and evidence, identifying critical nodes contributing to heightened risks, aiding in the formulation of risk management strategies. Application to two urban bridges demonstrates the method’s effectiveness and robustness, positioning it as a valuable decision-making tool for bridge safety risk management.https://doi.org/10.1038/s41598-025-15235-x |
| spellingShingle | Zhong Cao Weicong He Kaihong Chen Rui Rao Zhaohui Chen A robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian network Scientific Reports |
| title | A robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian network |
| title_full | A robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian network |
| title_fullStr | A robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian network |
| title_full_unstemmed | A robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian network |
| title_short | A robust method for bridge safety risk assessment using improved multi-state fuzzy Bayesian network |
| title_sort | robust method for bridge safety risk assessment using improved multi state fuzzy bayesian network |
| url | https://doi.org/10.1038/s41598-025-15235-x |
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