American Psychological Association 6th edition

Danach, K., Khalaf, A. H., Rammal, A., & Harb, H. (2024). Enhancing DDBMS Performance through RFO-SVM Optimized Data Fragmentation: A Strategic Approach to Machine Learning Enhanced Systems. Applied Sciences (2076-3417), 14(14), 6093-6122. https://doi.org/10.3390/app14146093

ISO-690 (author-date, English)

DANACH, Kassem, KHALAF, Abdullah Hussein, RAMMAL, Abbas und HARB, Hassan, 2024. Enhancing DDBMS Performance through RFO-SVM Optimized Data Fragmentation: A Strategic Approach to Machine Learning Enhanced Systems. Applied Sciences (2076-3417). 15 Juli 2024. Vol. 14, no. 14, p. 6093-6122. DOI 10.3390/app14146093.

Modern Language Association 9th edition

Danach, K., A. H. Khalaf, A. Rammal, und H. Harb. „Enhancing DDBMS Performance through RFO-SVM Optimized Data Fragmentation: A Strategic Approach to Machine Learning Enhanced Systems.“. Applied Sciences (2076-3417), Bd. 14, Nr. 14, Juli 2024, S. 6093-22, https://doi.org/10.3390/app14146093.

Mohr Siebeck - Recht (Deutsch - Österreich)

Danach, Kassem/Khalaf, Abdullah Hussein/Rammal, Abbas/Harb, Hassan: Enhancing DDBMS Performance through RFO-SVM Optimized Data Fragmentation: A Strategic Approach to Machine Learning Enhanced Systems., Applied Sciences (2076-3417) 2024, 6093-6122.

Emerald - Harvard

Danach, K., Khalaf, A.H., Rammal, A. und Harb, H. (2024), „Enhancing DDBMS Performance through RFO-SVM Optimized Data Fragmentation: A Strategic Approach to Machine Learning Enhanced Systems.“, Applied Sciences (2076-3417), Vol. 14 No. 14, S. 6093-6122.

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