Shang, Z., Zhao, Z., Yan, R. und Chen, X. (2023) „Core loss: Mining core samples efficiently for robust machine anomaly detection against data pollution.“, Mechanical Systems & Signal Processing, 189, S. N.PAG-0. doi:10.1016/j.ymssp.2022.110046.
Chicago Manual of Style 17th edition (full note)Shang, Zuogang, Zhibin Zhao, Ruqiang Yan, und Xuefeng Chen. „Core Loss: Mining Core Samples Efficiently for Robust Machine Anomaly Detection Against Data Pollution.“. Mechanical Systems & Signal Processing 189 (15. April 2023): N.PAG-0. https://doi.org/10.1016/j.ymssp.2022.110046.
American Psychological Association 7th editionShang, Z., Zhao, Z., Yan, R., & Chen, X. (2023). Core loss: Mining core samples efficiently for robust machine anomaly detection against data pollution. Mechanical Systems & Signal Processing, 189, N.PAG-0. https://doi.org/10.1016/j.ymssp.2022.110046
Modern Language Association 9th editionShang, Z., Z. Zhao, R. Yan, und X. Chen. „Core Loss: Mining Core Samples Efficiently for Robust Machine Anomaly Detection Against Data Pollution.“. Mechanical Systems & Signal Processing, Bd. 189, April 2023, S. N.PAG-0, https://doi.org/10.1016/j.ymssp.2022.110046.
ISO-690 (author-date, Deutsch)SHANG, Zuogang, Zhibin ZHAO, Ruqiang YAN und Xuefeng CHEN, 2023. Core loss: Mining core samples efficiently for robust machine anomaly detection against data pollution. Mechanical Systems & Signal Processing. 15 April 2023. Bd. 189, , S. N.PAG-0. DOI 10.1016/j.ymssp.2022.110046