Open AccessComparison and Adaptation of Two Strategies for Anomaly Detection in Load Profiles Based on Methods from the Fields of Machine Learning and Statistics
Author(s) -
Patrick Krawiec,
Mark Junge,
Jens Hesselbach
Publication year - 2021
Publication title -
open journal of energy efficiency
Language(s) - English
Resource type - Journals
eISSN - 2169-2637
pISSN - 2169-2645
DOI - 10.4236/ojee.2020.102003
Subject(s) - anomaly detection , exponential smoothing , anomaly (physics) , statistics , mathematics , smoothing , artificial neural network , standard deviation , sample (material) , studentized range , data mining , algorithm , computer science , artificial intelligence , physics , condensed matter physics , thermodynamics
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