American Psychological Association 6th edition

Palomares-Salas, J. C., Aguado-González, S., & Sierra-Fernández, J. M. (2025). Robustness of Machine Learning and Deep Learning Models for Power Quality Disturbance Classification: A Cross-Platform Analysis. Applied Sciences (2076-3417), 15(19), 10602-10617. https://doi.org/10.3390/app151910602

ISO-690 (author-date, English)

PALOMARES-SALAS, José Carlos, AGUADO-GONZÁLEZ, Sergio und SIERRA-FERNÁNDEZ, José María, 2025. Robustness of Machine Learning and Deep Learning Models for Power Quality Disturbance Classification: A Cross-Platform Analysis. Applied Sciences (2076-3417). 1 Oktober 2025. Vol. 15, no. 19, p. 10602-10617. DOI 10.3390/app151910602.

Modern Language Association 9th edition

Palomares-Salas, J. C., S. Aguado-González, und J. M. Sierra-Fernández. „Robustness of Machine Learning and Deep Learning Models for Power Quality Disturbance Classification: A Cross-Platform Analysis.“. Applied Sciences (2076-3417), Bd. 15, Nr. 19, Oktober 2025, S. 10602-17, https://doi.org/10.3390/app151910602.

Mohr Siebeck - Recht (Deutsch - Österreich)

Palomares-Salas, José Carlos/Aguado-González, Sergio/Sierra-Fernández, José María: Robustness of Machine Learning and Deep Learning Models for Power Quality Disturbance Classification: A Cross-Platform Analysis., Applied Sciences (2076-3417) 2025, 10602-10617.

Emerald - Harvard

Palomares-Salas, J.C., Aguado-González, S. und Sierra-Fernández, J.M. (2025), „Robustness of Machine Learning and Deep Learning Models for Power Quality Disturbance Classification: A Cross-Platform Analysis.“, Applied Sciences (2076-3417), Vol. 15 No. 19, S. 10602-10617.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.