A novel approach for the detection of anomalous energy consumption patterns in industrial cyber‐physical systems-Reference-Cited by-同舟云学术

A novel approach for the detection of anomalous energy consumption patterns in industrial cyber‐physical systems

Published:2022-02-25 Issue: Volume: Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Mendia Izaskun¹^ORCID,Gil‐Lopez Sergio¹^ORCID,Grau Iñaki²,Del Ser Javier¹³^ORCID

Affiliation:

1. ICT Division TECNALIA, Basque Research and Technology Alliance (BRTA) Derio Spain

2. Department of Energy Efficiency GESTAMP Madrid Spain

3. Department of Communications Engineering University of the Basque Country (UPV/EHU) Bilbao Spain

Funder

Eusko Jaurlaritza

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12959

Reference79 articles.

1. Outlier Analysis

2. Survey on anomaly detection using data mining techniques;Agrawal S.;Procedia Computer Science,2015

3. A novel outlier detection method for multivariate data;Almardeny Y.;IEEE Transactions on Knowledge and Data Engineering,2020

4. Toward explainable deep neural network based anomaly detection;Amarasinghe K.;2018 11th international conference on human system interaction (hsi),2018

5. A linear method for deviation detection in large databases;Arning A.;Proceedings of the Second International Conference on Knowledge Discovery And Data Mining,1996

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