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- W4320802356 abstract "The emergence of fully automatic operation (FAO) system realizes the automation of the whole process of train operation and improves the overall automation level and system performance. In order to predict the possible faults of the system in operation, facilitate relevant personnel to formulate risk control measures, explore the causes of risk events, and carry out early prevention of accidents. In this paper, a fault prediction method based on ontology and Bayesian reasoning is proposed: firstly, the class in a specific scenario, the attribute relationship of the class and the case model are defined based on ontology to describe the interaction behavior and scenario parameters between subsystems; Then, according to the concepts described in the ontology model - the relationship between concepts, the Bayesian network topology is established to qualitatively describe the relationship between nodes, and the conditional probability distribution between network nodes is determined according to the historical fault data and expert experience; Finally, the proposed method is verified by an actual fault case of Yanfang line." @default.
- W4320802356 created "2023-02-15" @default.
- W4320802356 creator A5060175935 @default.
- W4320802356 creator A5074984852 @default.
- W4320802356 date "2022-08-15" @default.
- W4320802356 modified "2023-10-01" @default.
- W4320802356 title "Research on Fault Prediction of Fully Automatic Operation System Based on Ontology and Bayesian Network" @default.
- W4320802356 cites W2964144403 @default.
- W4320802356 doi "https://doi.org/10.1109/ccdc55256.2022.10033670" @default.
- W4320802356 hasPublicationYear "2022" @default.
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