Proposing a new local density estimation outlier detection algorithm: an empirical case study on flow pattern experiments
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition
Link
https://link.springer.com/content/pdf/10.1007/s10044-021-01019-2.pdf
Reference46 articles.
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2. Mahmoodi K, Ghassemi H (2018) Outlier detection in ocean wave measurements by using unsupervised data mining methods. Polish Marit Res 25:44–50. https://doi.org/10.2478/pomr-2018-0005
3. Tolvi J (2004) Genetic algorithms for outlier detection and variable selection in linear regression models. Soft Comput 8:527–533. https://doi.org/10.1007/s00500-003-0310-2
4. Aljawarneh S, Aldwairi M, Yassein MB (2018) Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model. J Comput Sci 25:152–160. https://doi.org/10.1016/j.jocs.2017.03.006
5. Greggio N (2018) Anomaly Detection in IDSs by means of unsupervised greedy learning of finite mixture models. Soft Comput 22:3357–3372. https://doi.org/10.1007/s00500-017-2581-z
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