Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Youssef Safi"'
Autor:
Abdelaziz Bouroumi, Youssef Safi
Publikováno v:
Scopus-Elsevier
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef28983f0943ddc9abe9ca3df3a43efb
https://doi.org/10.12988/ams.2013.13025
https://doi.org/10.12988/ams.2013.13025
Publikováno v:
Applied Mathematical Sciences. 7:4415-4423
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be5dd0fc759a25c845ae8e87fd112493
https://doi.org/10.12988/ams.2013.35293
https://doi.org/10.12988/ams.2013.35293
Autor:
Abdelaziz Bouroumi, Youssef Safi
Publikováno v:
2014 Second World Conference on Complex Systems (WCCS).
We propose an evolutionary algorithm for optimizing both the topology and the synaptic weights of single hidden-layer feed-forward neural networks (SLFNs). We introduce new evolutionary operators of recombination and mutation we designed for evolving
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ac99244b3a3018f7457dc6a484c6c2f
https://doi.org/10.1109/icocs.2014.7060901
https://doi.org/10.1109/icocs.2014.7060901
Publikováno v:
2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA).
In this paper, we present a semi-fuzzy collaborative algorithm for detecting the optimal number of clusters in a given data set of unlabeled objects. This algorithm is based on a measure of inter-points similarity that allows the detection and creati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2cbca341140ee256f942f71d280f723
https://doi.org/10.1109/sita.2013.6560795
https://doi.org/10.1109/sita.2013.6560795
Autor:
Abdelaziz Bouroumi, Youssef Safi
Publikováno v:
ICMCS
We propose an evolutionary algorithm for optimizing the hidden layer size of three-layer perceptrons. The optimization problem is posed in terms of finding, for each learning database, the best number of neurons to use in the hidden layer. For this,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d84dafe78153927fdceea106b4da6c9a
https://doi.org/10.1109/icmcs.2012.6320227
https://doi.org/10.1109/icmcs.2012.6320227
Autor:
Youssef Safi, Abdelaziz Bouroumi
Publikováno v:
2011 International Conference on Multimedia Computing and Systems.
In this paper, we present an application of artificial neural networks to the real-world problem of predicting forest fire. The neural network used for this application is a multilayer perceptron whose architectural parameters, i.e., the number of hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89ab4d6d9f4b8d93137e8d6428cbb8bf
https://doi.org/10.1109/icmcs.2011.5945716
https://doi.org/10.1109/icmcs.2011.5945716
Autor:
Youssef Safi, Abdelaziz Bouroumi
Publikováno v:
Scopus-Elsevier
We propose an evolutionary method for optimising both the architecture and the synaptic weights of single hidden-layer feed forward neural networks. Based on evolutionary strategies, this method uses new genetic operators of mutation and recombinatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::791b3b3ef96680945fba11404f51fc31
https://doi.org/10.1504/ijica.2014.066497
https://doi.org/10.1504/ijica.2014.066497