Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Rafael Rivera-Lopez"'
Publikováno v:
IEEE Access, Vol 12, Pp 169850-169868 (2024)
The growing demand for complex machine learning models has increased the use of black-box models, such as random forests and artificial neural networks, posing significant challenges regarding explainability and interpretability. This manuscript addr
Externí odkaz:
https://doaj.org/article/e144ce46734a4c70b948e857ecf8bb30
Autor:
Marta Lilia Erana-Diaz, Marco Antonio Cruz-Chavez, Rafael Rivera-Lopez, Beatriz Martinez-Bahena, Erika Yesenia Avila-Melgar, Martin Heriberto Cruz-Rosales
Publikováno v:
IEEE Access, Vol 8, Pp 117063-117079 (2020)
In this paper, a computational methodology combining the simulated annealing algorithm with two machine learning techniques to select a near-optimal safeguard set for business risk response is presented. First, a mathematical model with four types of
Externí odkaz:
https://doaj.org/article/24ba6df4c2484129a496f4a5ebc76c16
Autor:
Rafael Rivera-Lopez, Juana Canul-Reich
Publikováno v:
IEEE Access, Vol 6, Pp 5548-5563 (2018)
In this paper, a differential-evolution-based approach implementing a global search strategy to find a near-optimal axis-parallel decision tree is introduced. In this paper, the internal nodes of a decision tree are encoded in a real-valued chromosom
Externí odkaz:
https://doaj.org/article/d685653751e343fd9264ffc17a407f08
Autor:
Jesús Francisco Perez-Gomez, Juana Canul-Reich, Rafael Rivera-Lopez, Betania Hernández Ocaña, Cristina López-Ramírez
Publikováno v:
Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences ISBN: 9789811987410
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d327de5459ff68eaa93c4b1287994e4
https://doi.org/10.1007/978-981-19-8742-7_41
https://doi.org/10.1007/978-981-19-8742-7_41
Grid-Based Hybrid Genetic Approach to Relaxed Flexible Flow Shop with Sequence-Dependent Setup Times
Autor:
Erika Yesenia Avila Melgar, Marta Lilia Erana Diaz, Marco Antonio Cruz-Chavez, Martin H. Cruz-Rosales, Fredy Juarez-Perez, Rafael Rivera-Lopez
Publikováno v:
Applied Sciences; Volume 12; Issue 2; Pages: 607
Applied Sciences, Vol 12, Iss 607, p 607 (2022)
Applied Sciences, Vol 12, Iss 607, p 607 (2022)
In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instances of the flexible flow shop scheduling problem with sequence-dependent setup times is introduced. The genetic algorithm takes advantage of the distribut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f2b7e171d67e5f0aa36d9b0bc0ad945
Publikováno v:
2010 IEEE Electronics, Robotics and Automotive Mechanics Conference.
This paper addresses the Job Shop Scheduling Problem (JSSP). Basic constraints are established and it is modeled by a disjunctive graph. The model was mapped to Unrelated Parallel Machines Problem through a bipartite graph. An analysis of constraints
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7f148353b49434df1681f42de61e776
https://doi.org/10.1109/cerma.2010.27
https://doi.org/10.1109/cerma.2010.27
Publikováno v:
Symmetry (20738994). Feb2023, Vol. 15 Issue 2, p271. 48p.
Publikováno v:
Women's Health Weekly; 7/4/2023, p522-522, 1p
Publikováno v:
Applied Sciences (2076-3417); Feb2023, Vol. 13 Issue 3, p1425, 231p
Publikováno v:
Women's Health Weekly; 10/10/2024, p320-320, 1p