Anomaly Detection in Dam Behaviour with Machine Learning Classification Models

Anomaly Detection in Dam Behaviour with Machine Learning Classification Models

Dam safety assessment is typically made by comparison between the outcome of some predictive model and measured monitoring data. This is done separately for each response variable, and the results are later interpreted before decision making. In this work, three approaches based on machine learning...

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Bibliographic Details
Main Authors: Fernando Salazar, André Conde, Joaquín Irazábal, David J. Vicente
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Water
Subjects:
anomaly detection
machine learning
support vector machines
random forest
one-class classification
Online Access:https://www.mdpi.com/2073-4441/13/17/2387

Internet

https://www.mdpi.com/2073-4441/13/17/2387

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