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Dynamic risk assessment of metro station with interval type-2 fuzzy set and TOPSIS method.

, , , , and . J. Intell. Fuzzy Syst., 29 (1): 93-106 (2015)

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Dynamic risk assessment of metro station with interval type-2 fuzzy set and TOPSIS method., , , , and . J. Intell. Fuzzy Syst., 29 (1): 93-106 (2015)Spectral Kurtosis Entropy and Weighted SaE-ELM for Bogie Fault Diagnosis under Variable Conditions., , , and . Sensors, 18 (6): 1705 (2018)A Multi-Dimension End-to-End CNN Model for Rotating Devices Fault Diagnosis on High-Speed Train Bogie., , , and . IEEE Trans. Veh. Technol., 69 (3): 2513-2524 (2020)Understanding real faults of axle box bearings based on vibration data using decision tree., , , and . ICPHM, page 1-5. IEEE, (2018)The Robust Multi-Scale Deep-SVDD Model for Anomaly Online Detection of Rolling Bearings., , , and . Sensors, 22 (15): 5681 (2022)SWDAE: A New Degradation State Evaluation Method for Metro Wheels With Interpretable Health Indicator Construction Based on Unsupervised Deep Learning., , , , and . IEEE Trans. Instrum. Meas., (2024)Rolling Element Bearing Fault Diagnosis under Impulsive Noise Environment Based on Cyclic Correntropy Spectrum., , , , and . Entropy, 21 (1): 50 (2019)A New Deep Tensor Autoencoder Network for Unsupervised Health Indicator Construction and Degradation State Evaluation of Metro Wheel., , , and . IEEE Trans. Instrum. Meas., (2023)Deep Domain-Adversarial Anomaly Detection With One-Class Transfer Learning., , , and . IEEE CAA J. Autom. Sinica, 10 (2): 524-546 (2023)Multistate Reliability Evaluation of Bogie on High Speed Railway Vehicle Based on the Network Flow Theory., , , and . Int. J. Softw. Eng. Knowl. Eng., 28 (4): 431-452 (2018)