Diverse activation functions based-hybrid RBF-ELM neural network for medical classification.

Autor: Siouda, Roguia, Nemissi, Mohamed, Seridi, Hamid

Publikováno v: Evolutionary Intelligence; Apr2024, Vol. 17 Issue 2, p829-845, 17p

A random deep neural system for heartbeat classification.

Autor: Siouda, Roguia, Nemissi, Mohamed, Seridi, Hamid

Publikováno v: Evolving Systems; Feb2023, Vol. 14 Issue 1, p37-48, 12p

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The Labeled Classification and Its Application

Autor: Nemissi, Mohamed, Seridi, Hamid, Akdag, Herman

Publikováno v: International Journal of Computational Intelligence
International Journal of Computational Intelligence, 2008, 2 (6), pp.2088-2097
International Journal of Computational Intelligence, World Academy of Science, Engineering and Technology, 2008, 2 (6), pp.2088-2097

This paper presents and evaluates a new classification method that aims to improve classifiers performances and speed up their training process. The proposed approach, called labeled classification, seeks to improve convergence of the BP (Back propag

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c231f8e1b28bac1055ba05109f266a1
https://hal.science/hal-01336163

Unsupervised Automatic Classification by C-Means : Resolution of Initialisation Problem

Autor: Boudouda, Houria, Nemissi, Mohamed, Seridi, Hamid, Akdag, Herman

Publikováno v: Al-Azhar Engineering University Journal, AEUJ
Al-Azhar Engineering University Journal, AEUJ, 2005, 8 (7), pp.72-79

National audience

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::e4a6bdfb3b956c3aa1a9d7f2b6a51646
https://hal.archives-ouvertes.fr/hal-01171066