Outlier Identification of Concrete Dam Displacement Monitoring Data Based on WAVLET-DBSCAN-IFRL

Monitoring data outliers comprises isolated mode outliers, cluster mode outliers, and normal points. To identify and distinguish the data hopping problems caused by outliers and environmental mutations in the displacement monitoring data of concrete AMS, this paper proposes a method based on wavelet...

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Bibliographic Details
Published in:	Water (Basel) Vol. 17; no. 5; p. 716
Main Authors:	Fang, Chunhui, Wang, Xue, Hu, Weixing, He, Xiaojun, Huang, Zihui, Gu, Hao
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.03.2025
Subjects:	Accuracy Algorithms Analysis China Cluster analysis Clustering Concrete Dams Data analysis Data mining Forests Machine learning New Jersey Principal components analysis Time series Water levels Wavelet transforms China New Jersey
ISSN:	2073-4441, 2073-4441
Online Access:	Get full text
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