Kernel Function Selection for FISVDD Applied to Outliers Detection Application for Energy Time Series Datasets-Reference-Cited by-同舟云学术

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Kernel Function Selection for FISVDD Applied to Outliers Detection Application for Energy Time Series Datasets

Published:2024-05-16 Issue: Volume: Page:1-16
ISSN:1532-5008
Container-title:Electric Power Components and Systems
language:en
Short-container-title:Electric Power Components and Systems

Author:

Amalou Ibtissam¹²,Mouhni Naoual³²,Abdali Abdelmounaim¹

Affiliation:

1. Department of Physics, CISIEV, FSTG, University Cadi Ayyad, Marrakech, Morocco

2. Department of Computer Science, LAMIGEP, EMSI Marrakech, Marrakech, Morocco

3. Department of Computer Science, GL-ISI Team, Faculty of sciences and techniques of Errachidia, UMI Meknes, Meknes, Morocco

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15325008.2024.2350058

Reference30 articles.

1. A State-of-the-Art Review on Electric Power Systems and Digital Transformation

2. N. Mohamed and J. Cavallaro “Design and implementation of an FPGA-based DNN architecture for real-time outlier detection ” Journal of Signal Processing Systems vol. 51 pp. 845–861 2023. https://link.springer.com/article/10.1007/s11265-023-01835-1.

3. A multi-step outlier-based anomaly detection approach to network-wide traffic

4. Harmonic Distortions in Smart Devices: A Comprehensive Discussion on Challenges of Conventional and Future Smart IoT Devices

5. R. dos Santos Costa et al. “Data analysis techniques applied to distribution systems: a systematic mapping study ” Electric Power Components and Systems vol. 51 no. 5 pp. 452–467 2023. https://www.tandfonline.com/doi/full/10.1080/15325008.2023.2175927.

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