American Psychological Association 6th edition

Mahtal, B. E. D. N., Laidi, M., Rahal, S., Hentabli, M., & Hamadache, M. (2025). Predicting Pesticide LC50 Toxicity Using Convolutional Neural Networks and Dragonfly-Support Vector Machine Methods with Quantitative Structure-Activity Relationship and 2 D Molecular Fingerprints: A Case Study on Oncorhynchus Mykiss. Chemistry Africa: A Journal of the Tunisian Chemical Society, 8(4), 1463-1476. https://doi.org/10.1007/s42250-025-01239-7

ISO-690 (author-date, English)

MAHTAL, Badiet El Djamel Nedjma, LAIDI, Maamar, RAHAL, Soufiane, HENTABLI, Mohamed und HAMADACHE, Mabrouk, 2025. Predicting Pesticide LC50 Toxicity Using Convolutional Neural Networks and Dragonfly-Support Vector Machine Methods with Quantitative Structure-Activity Relationship and 2 D Molecular Fingerprints: A Case Study on Oncorhynchus Mykiss. Chemistry Africa: A Journal of the Tunisian Chemical Society. 1 Mai 2025. Vol. 8, no. 4, p. 1463-1476. DOI 10.1007/s42250-025-01239-7.

Modern Language Association 9th edition

Mahtal, B. E. D. N., M. Laidi, S. Rahal, M. Hentabli, und M. Hamadache. „Predicting Pesticide LC50 Toxicity Using Convolutional Neural Networks and Dragonfly-Support Vector Machine Methods With Quantitative Structure-Activity Relationship and 2 D Molecular Fingerprints: A Case Study on Oncorhynchus Mykiss“. Chemistry Africa: A Journal of the Tunisian Chemical Society, Bd. 8, Nr. 4, Mai 2025, S. 1463-76, https://doi.org/10.1007/s42250-025-01239-7.

Mohr Siebeck - Recht (Deutsch - Österreich)

Mahtal, Badiet El Djamel Nedjma/Laidi, Maamar/Rahal, Soufiane/Hentabli, Mohamed/Hamadache, Mabrouk: Predicting Pesticide LC50 Toxicity Using Convolutional Neural Networks and Dragonfly-Support Vector Machine Methods with Quantitative Structure-Activity Relationship and 2 D Molecular Fingerprints: A Case Study on Oncorhynchus Mykiss, Chemistry Africa: A Journal of the Tunisian Chemical Society 2025, 1463-1476.

Emerald - Harvard

Mahtal, B.E.D.N., Laidi, M., Rahal, S., Hentabli, M. und Hamadache, M. (2025), „Predicting Pesticide LC50 Toxicity Using Convolutional Neural Networks and Dragonfly-Support Vector Machine Methods with Quantitative Structure-Activity Relationship and 2 D Molecular Fingerprints: A Case Study on Oncorhynchus Mykiss“, Chemistry Africa: A Journal of the Tunisian Chemical Society, Vol. 8 No. 4, S. 1463-1476.

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