1. Equipment maintenance and repair system. Terms and definitions: national standard of the Russian Federation. (2017). Standard No. GOST 18322–2016. Moscow: Standartinform. [in Russian language]
2. Gupta M., Gao J., Aggarwal C. C., Han J. (2014). Outlier Detection for Temporal Data: A Survey. IEEE Transactions on Knowledge and Data Engineering, 26(9), 2250 – 2267. DOI: 10.1109/TKDE.2013.184
3. Cai X., Aydin B., Maydeo S. et al. (2020). Local Outlier Detection for Multi-Type Spatio-Temporal Trajectories. IEEE International Conference on Big Data, 4509 – 4518. Atlanta. DOI: 10.1109/BigData50022.2020.9377801
4. Yu K., Shi W., Santoro N., Ma X. (2019). Real-Time Outlier Detection Over Streaming Data. 2019 IEEE SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, 125 – 132. Leicester. DOI: 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00063
5. Cao K., Liu Y., Meng G. et al. (2020). Trajectory Outlier Detection on Trajectory Data Streams. IEEE Access, 8, 34187 – 34196. DOI: 10.1109/ACCESS.2020.2974521
6. Cai X., Aydin B., Ji A., Angryk R. (2021). A Framework for Local Outlier Detection from Spatio-Temporal Trajectory Datasets. 25th International Conference on Pattern Recognition (ICPR), 5682 – 5689. Milan. DOI: 10.1109/ICPR48806.2021.9412274
7. Wang Y., Qin K., Sun H., Lu B. (2021). Spatial-Temporal Analysis of High Plateau Flight Turning Procedure Exceptions Based on QAR Data. IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT), 62 – 64. Changsha. DOI: 10.1109/ICCASIT53235.2021.9633729
8. Song Y., Yu J., Tang D. et al. (2020). Telemetry Data-Based Spacecraft Anomaly Detection Using Generative Adversarial Networks. International Conference on Sensing, Measurement & Data Analytics in the Era of Artificial Intelligence (ICSMD), 297 – 301. Xi'an. DOI: 10.1109/ICSMD50554.2020.9261736
9. Pu J., Wang Y., Liu X., Zhang X. (2019). STLP-OD: Spatial and Temporal Label Propagation for Traffic Outlier Detection. IEEE Access, 7, 63036 – 63044. DOI: 10.1109/ACCESS.2019.2916853
10. Fitters W., Cuzzocrea A., Hassani M. (2021). Enhancing LSTM Prediction of Vehicle Traffic Flow Data via Outlier Correlations. IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 210 – 217. Madrid. DOI: 10.1109/COMPSAC51774.2021.00039
11. Al Samara M., Bennis I., Abouaissa A., Lorenz P. (2021). An Efficient Outlier Detection and Classification Clustering-Based Approach for WSN. IEEE Global Communications Conference (GLOBECOM), 1 – 6. Madrid. DOI: 10.1109/GLOBECOM46510.2021.9685756
12. Haj-Hassan A., Habib C., Nassar J. (2020). Real-Time Spatio-Temporal Based Outlier Detection Framework for Wireless Body Sensor Networks. IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 1 – 6. New Delhi. DOI: 10.1109/ANTS50601.2020.9342827.
13. Al Samara M., Bennis I., Abouaissa A., Lorenz P. (2022). OPTICS-Based Outlier Detection with Newton Classification. International Wireless Communications and Mobile Computing (IWCMC), 784 – 789. Dubrovnik. DOI: 10.1109/IWCMC55113.2022.9825224
14. Zhang H., Li Z. (2019). Anomaly Detection Approach for Urban Sensing Based on Credibility and Time-Series Analysis Optimization Model. IEEE Access, 7, 49102 – 49110. DOI: 10.1109/ACCESS.2019.2909967
15. Mo R., Pay Y., Venkatarayalu N.V. et al. (2023). Unsupervised TCN-AE-Based Outlier Detection for Time Series with Seasonality and Trend for Cellular Networks. IEEE Transactions on Wireless Communications, 22(5), 3114 – 3127. DOI: 10.1109/TWC.2022.3216004
16. Dridi A., Boucetta C., Hammami S.E. et al. (2021). STAD: Spatio-Temporal Anomaly Detection Mechanism for Mobile Network Management. IEEE Transactions on Network and Service Management, 18(1), 894 – 906. DOI: 10.1109/TNSM.2020.3048131
17. Mo R., Pei Y., Venkatarayalu N. et al. (2021). An Unsupervised TCN-Based Outlier Detection for Time Series with Sea-sonality and Trend. IEEE VTS 17th Asia Pacific Wireless Communications Symposium (APWCS), 1 – 5. Osaka. DOI: 10.1109/APWCS50173.2021.9548759
18. Borah A., Gruenwald L., Leal E., Panjei E. (2021). A GPU Algorithm for Detecting Contextual Outliers in Multiple Concurrent Data Streams. IEEE International Conference on Big Data (Big Data), 2737 – 2742. Orlando. DOI: 10.1109/BigData52589.2021.9671460
19. Lu W., Cheng Y., Xiao C. et al. (2017). Unsupervised Sequential Outlier Detection with Deep Architectures. IEEE Transactions on Image Processing, 26(9), 4321 – 4330. DOI: 10.1109/TIP.2017.2713048
20. Suetin P. K. (2007). Classical orthogonal polynomials. Moscow: Fizmatlit. [in Russian language]
21. Nikiforov A. F., Suslov S. K. (1985). Classical orthogonal polynomials. Moscow: Znanie. [in Russian language]