American Psychological Association 6th edition

Kallel, A., Rekik, M., & Khemakhem, M. (2021). Hybrid-based framework for COVID-19 prediction via federated machine learning models. The Journal of Supercomputing: An International Journal of High-Performance Computer Design, Analysis, and Use, 1-28. https://doi.org/10.1007/s11227-021-04166-9

ISO-690 (author-date, English)

KALLEL, Ameni, REKIK, Molka und KHEMAKHEM, Mahdi, 2021. Hybrid-based framework for COVID-19 prediction via federated machine learning models. The Journal of Supercomputing: An International Journal of High-Performance Computer Design, Analysis, and Use. 5 November 2021. P. 1-28. DOI 10.1007/s11227-021-04166-9.

Modern Language Association 9th edition

Kallel, A., M. Rekik, und M. Khemakhem. „Hybrid-Based Framework for COVID-19 Prediction via Federated Machine Learning Models“. The Journal of Supercomputing: An International Journal of High-Performance Computer Design, Analysis, and Use, November 2021, S. 1-28, https://doi.org/10.1007/s11227-021-04166-9.

Mohr Siebeck - Recht (Deutsch - Österreich)

Kallel, Ameni/Rekik, Molka/Khemakhem, Mahdi: Hybrid-based framework for COVID-19 prediction via federated machine learning models, The Journal of Supercomputing: An International Journal of High-Performance Computer Design, Analysis, and Use 2021, 1-28.

Emerald - Harvard

Kallel, A., Rekik, M. und Khemakhem, M. (2021), „Hybrid-based framework for COVID-19 prediction via federated machine learning models“, The Journal of Supercomputing: An International Journal of High-Performance Computer Design, Analysis, and Use, S. 1-28.

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