Elish, M.O. und Elish, K. (2021) „An Empirical Comparison of Resampling Ensemble Methods of Deep Learning Neural Networks for Cross-Project Software Defect Prediction.“, International Journal of Intelligent Engineering & Systems, 14(3), S. 201-209. doi:10.22266 jies2021.0630.18.
Chicago Manual of Style 17th edition (full note)Elish, Mahmoud O., und Karim Elish. „An Empirical Comparison of Resampling Ensemble Methods of Deep Learning Neural Networks for Cross-Project Software Defect Prediction.“. International Journal of Intelligent Engineering & Systems 14, Nr. 3 (1. Mai 2021): 201-9. https://doi.org/10.22266 jies2021.0630.18.
American Psychological Association 7th editionElish, M. O., & Elish, K. (2021). An Empirical Comparison of Resampling Ensemble Methods of Deep Learning Neural Networks for Cross-Project Software Defect Prediction. International Journal of Intelligent Engineering & Systems, 14(3), 201-209. https://doi.org/10.22266 jies2021.0630.18
Modern Language Association 9th editionElish, M. O., und K. Elish. „An Empirical Comparison of Resampling Ensemble Methods of Deep Learning Neural Networks for Cross-Project Software Defect Prediction.“. International Journal of Intelligent Engineering & Systems, Bd. 14, Nr. 3, Mai 2021, S. 201-9, https://doi.org/10.22266 jies2021.0630.18.
ISO-690 (author-date, Deutsch)ELISH, Mahmoud O. und Karim ELISH, 2021. An Empirical Comparison of Resampling Ensemble Methods of Deep Learning Neural Networks for Cross-Project Software Defect Prediction. International Journal of Intelligent Engineering & Systems. 1 Mai 2021. Bd. 14, Nr. 3, S. 201-209. DOI 10.22266 jies2021.0630.18