Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Saul Zapotecas-Martinez"'
Autor:
Israel Miguel-Andres, Jorge Ramos-Frutos, Marwa Sharawi, Diego Oliva, Elivier Reyes-Davila, Angel Casas-Ordaz, Marco Perez-Cisneros, Saul Zapotecas-Martinez
Publikováno v:
IEEE Access, Vol 12, Pp 22433-22447 (2024)
Musculoskeletal disorders of the foot are a common complaint in the population. It has been found a flatfoot prevalence of 13.6% in young adults and a prevalence of 26.62% in adults between 42 and 91 years. Different non-invasive techniques can ident
Externí odkaz:
https://doaj.org/article/cb6f31cd05924f95ac541ef4505938fa
Autor:
Israel Miguel-Andres, Jorge Ramos-Frutos, Marwa Sharawi, Diego Oliva, Elivier Reyes-Davila, Angel Casas-Ordaz, Marco Perez-Cisneros, Saul Zapotecas-Martinez
Publikováno v:
IEEE Access, Vol 12, Pp 158877-158877 (2024)
Presents corrections to the paper, (Corrections to “Wrapper-Based Feature Selection to Classify Flatfoot Disease”).
Externí odkaz:
https://doaj.org/article/31d550e9ea864149b9924779d6a6ad4b
Autor:
Adriana Menchaca-Mendez, Elizabeth Montero, Luis Miguel Antonio, Saul Zapotecas-Martinez, Carlos A. Coello Coello, Maria-Cristina Riff
Publikováno v:
IEEE Access, Vol 7, Pp 18267-18283 (2019)
Convergence and diversity of solutions play an essential role in the design of multi-objective evolutionary algorithms (MOEAs). Among the available diversity mechanisms, the $\epsilon $ -dominance has shown a proper balance between convergence and di
Externí odkaz:
https://doaj.org/article/ece314f911f2436d899969ed4f79b1c6
Publikováno v:
IEEE Access, Vol 6, Pp 63382-63401 (2018)
One of the main disadvantages of evolutionary multi-objective algorithms (EMOAs) based on hypervolume is the computational cost of the hypervolume computation. This deficiency gets worse either when an EMOA calculates the hypervolume several times or
Externí odkaz:
https://doaj.org/article/523313f999f74ce3a9f4f6a39c71073b
Publikováno v:
Mathematics, Vol 10, Iss 1, p 19 (2021)
One of the major limitations of evolutionary algorithms based on the Lebesgue measure for multi-objective optimization is the computational cost required to approximate the Pareto front of a problem. Nonetheless, the Pareto compliance property of the
Externí odkaz:
https://doaj.org/article/fdf8aa9514d14f57a7fe41e9930b001f
Autor:
VICTOR HUGO ESCANDON BAILON
Publikováno v:
Universidad Autónoma Metropolitana
UAM
Repositorio Institucional de la UAM Iztapalapa
UAM
Repositorio Institucional de la UAM Iztapalapa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed37b2a36a0e03385a2f235fc8577a1d
https://doi.org/10.24275/uami.dv13zt31f
https://doi.org/10.24275/uami.dv13zt31f
