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http://dx.doi.org/10.14346/JKOSOS.2022.37.1.78

A Study on the Risk Assessment for Urban Railway Systems Using an Adaptive Neuro-Fuzzy Inference System(ANFIS)  

Tak, Kil Hun (Department of railway Safety Engineering, Seoul National University of Science & Technology)
Koo, Jeong Seo (Department of railway Safety Engineering, Seoul National University of Science & Technology)
Publication Information
Journal of the Korean Society of Safety / v.37, no.1, 2022 , pp. 78-87 More about this Journal
Abstract
In the risk assessment of urban railway systems, a hazard log is created by identifying hazards from accident and failure data. Then, based on a risk matrix, evaluators analyze the frequency and severity of the occurrence of the hazards, conduct the risk assessment, and then establish safety measures for the risk factors prior to risk control. However, because subjective judgments based on the evaluators' experiences affect the risk assessment results, a more objective and automated risk assessment system must be established. In this study, we propose a risk assessment model in which an adaptive neuro-fuzzy inference system (ANFIS), which is combined in artificial neural networks (ANN) and fuzzy inference system (FIS), is applied to the risk assessment of urban railway systems. The newly proposed model is more objective and automated, alleviating the limitations of risk assessments that use a risk matrix. In addition, the reliability of the model was verified by comparing the risk assessment results and risk control priorities between the newly proposed ANFIS-based risk assessment model and the risk assessment using a risk matrix. Results of the comparison indicate that a high level of accuracy was demonstrated in the risk assessment results of the proposed model, and uncertainty and subjectivity were mitigated in the risk control priority.
Keywords
risk assessment; risk matrix; adaptive Neuro-Fuzzy inference system (ANFIS);
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 "Railroad Safety Act", Act No.16395, Ministry of Land, Infrastructure and Transport(ROK), 2019.
2 "Guide Line of Risk Assessment for Railway", Ministry of Land, Infrastructure and Transport(ROK), 2018.
3 IEC 62278, "Railway Applications-The Specifications and Demonstration of Reliability, Availability, Maintainability and Safety(RAMS)", CENELEC, 2017.
4 J. B. Wang, K. J. Choi and C. W. Park, "Establishment of Risk Analysis and Assessment System for Railway Accidents and Hazards", Ministry of Land, Transport and Maritime Affairs(ROK), 2011.
5 J. S. Roger Jang, "Neuro-Fuzzy and Soft Computing", Prentice Hall, 1997.
6 S. Boran and S. H. Gokler, "A Novel FMEA Model Using Hybrid ANFIS-Taguchi Method", Arabian Journal for Science and Engineering 45, pp. 2131-214, 2020.   DOI
7 MIL-STD-882d, "Standard Practice for System Safety", Department of Defence(USA), 2000.
8 Report of Risk Assessment, Seoul Metro, 2019.
9 H. K. Yang and J. W. Lee, "A Study on SIL Allocation for Signaling Function with Fuzzy Risk Graph", Journal of the Korean Society for Railway, Vol. 19, No. 2, pp. 145-158, 2016.   DOI
10 K. W. Kim, J. U. Kim and H. H. Yoo, "Estimation of Distribution Demand for an Urban Rail Transit by Using the Adaptive Neuro-Fuzzy Inference System", Journal of the Korean Society of Civil Engineers, Vol. 27(2D), pp. 171-178, 2007.
11 Y. S. Kim, "The Study of Risk Matrix Development for Urban Metro EMU", Journal of the KOSOS, Vol. 26, No. 6, pp. 111-117, 2011.