Cite Them Right 11th edition - Harvard

Chawla, M. und Pareek, M. (2024) „Hybridizing Intelligence: A Comparative Study of Machine Learning Algorithm and ANN-PSO Deep Learning Model for Software Effort Estimation.“, International Journal of Performability Engineering, 20(11), S. 668-675. doi:10.23940 jpe.24.11.p3.668675.

Chicago Manual of Style 17th edition (full note)

Chawla, Meenakshi, und Meenakshi Pareek. „Hybridizing Intelligence: A Comparative Study of Machine Learning Algorithm and ANN-PSO Deep Learning Model for Software Effort Estimation.“. International Journal of Performability Engineering 20, Nr. 11 (1. November 2024): 668-75. https://doi.org/10.23940 jpe.24.11.p3.668675.

American Psychological Association 7th edition

Chawla, M., & Pareek, M. (2024). Hybridizing Intelligence: A Comparative Study of Machine Learning Algorithm and ANN-PSO Deep Learning Model for Software Effort Estimation. International Journal of Performability Engineering, 20(11), 668-675. https://doi.org/10.23940 jpe.24.11.p3.668675

Modern Language Association 9th edition

Chawla, M., und M. Pareek. „Hybridizing Intelligence: A Comparative Study of Machine Learning Algorithm and ANN-PSO Deep Learning Model for Software Effort Estimation.“. International Journal of Performability Engineering, Bd. 20, Nr. 11, November 2024, S. 668-75, https://doi.org/10.23940 jpe.24.11.p3.668675.

ISO-690 (author-date, Deutsch)

CHAWLA, Meenakshi und Meenakshi PAREEK, 2024. Hybridizing Intelligence: A Comparative Study of Machine Learning Algorithm and ANN-PSO Deep Learning Model for Software Effort Estimation. International Journal of Performability Engineering. 1 November 2024. Bd. 20, Nr. 11, S. 668-675. DOI 10.23940 jpe.24.11.p3.668675

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