RAJATHI, C. und PANJANATHAN, Rukmani, 2025. A Two-Phase Feature Selection Framework for Intrusion Detection System: Balancing Relevance and Computational Efficiency (2 P-FSID). Applied Artificial Intelligence. 1 Dezember 2025. Vol. 39, no. 1, p. 1-29. DOI 10.1080/08839514.2025.2539396.
Elsevier - Harvard (with titles)Rajathi, C., Panjanathan, R., 2025. A Two-Phase Feature Selection Framework for Intrusion Detection System: Balancing Relevance and Computational Efficiency (2 P-FSID). Applied Artificial Intelligence 39, 1-29. https://doi.org/10.1080/08839514.2025.2539396
American Psychological Association 7th editionRajathi, C., & Panjanathan, R. (2025). A Two-Phase Feature Selection Framework for Intrusion Detection System: Balancing Relevance and Computational Efficiency (2 P-FSID). Applied Artificial Intelligence, 39(1), 1-29. https://doi.org/10.1080/08839514.2025.2539396
Springer - Basic (author-date)Rajathi C, Panjanathan R (2025) A Two-Phase Feature Selection Framework for Intrusion Detection System: Balancing Relevance and Computational Efficiency (2 P-FSID).. Applied Artificial Intelligence 39:1-29. https://doi.org/10.1080/08839514.2025.2539396
Juristische Zitierweise (Stüber) (Deutsch)Rajathi, C./ Panjanathan, Rukmani, A Two-Phase Feature Selection Framework for Intrusion Detection System: Balancing Relevance and Computational Efficiency (2 P-FSID)., Applied Artificial Intelligence 2025, 1-29.