Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Shahla U. Umar"'
Autor:
Hero O. Ahmad, Shahla U. Umar
Publikováno v:
Informatica. 47
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d66b1b95e5bb0fe9a82d5536f1411fbd
https://doi.org/10.31449/inf.v47i5.4673
https://doi.org/10.31449/inf.v47i5.4673
Autor:
Aram M. Ahmed, Tarik A. Rashid, Soran Ab. M. Saeed, Kaniaw A. Noori, Bryar A. Hassan, Chnoor M Rahman, Omed H. Ahmed, Shahla U. Umar, Zaher Mundher Yaseen
This paper presents a multi-objective version of the Cat Swarm Optimization Algorithm called the Grid-based Multi-objective Cat Swarm Optimization Algorithm (GMOCSO). Convergence and diversity preservation are the two main goals pursued by modern mul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63a6ab26fdac4ba67343ccba285bd074
https://doi.org/10.21203/rs.3.rs-2882076/v1
https://doi.org/10.21203/rs.3.rs-2882076/v1
Autor:
Tarik A. Rashid, Shahla U. Umar
Publikováno v:
World Journal of Engineering. 18:606-620
In recent years several swarm optimization algorithms, such as Bat Algorithm (BA) have emerged, which was proposed by Xin-She Yang in 2010. The idea of the algorithm was taken from the echolocation ability of bats. Purpose: The purpose of this study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fdb6b5f3119a27a10940f889418d389
https://doi.org/10.1108/wje-10-2020-0495
https://doi.org/10.1108/wje-10-2020-0495
Autor:
Heja Sindi, Tarik A. Rashid, Nebojsa Bacanin, Abeer Alsadoon, Ahmed S. Shamsaldin, Shahla U. Umar, Chra I. Shekho Toghramchi, Mokhtar Mohammadi
Publikováno v:
Artificial Intelligence: Theory and Applications ISBN: 9783030727109
One popular example of metaheuristic algorithms from the swarm intelligence family is the Bat algorithm (BA). The algorithm was first presented in 2010 by Yang and quickly demonstrated its efficiency in comparison with other common algorithms. The BA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3950fb5c17b43af4355b9b57b50c130f
https://doi.org/10.1007/978-3-030-72711-6_9
https://doi.org/10.1007/978-3-030-72711-6_9
Publikováno v:
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience, Vol 2019 (2019)
Computational Intelligence and Neuroscience, Vol 2019 (2019)
Whale Optimization Algorithm (WOA) is a nature-inspired meta-heuristic optimization algorithm, which was proposed by Mirjalili and Lewis in 2016. This algorithm has shown its ability to solve many problems. Comprehensive surveys have been conducted a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d524cb31f81009ca4901505ff7925942
https://pubmed.ncbi.nlm.nih.gov/31231431
https://pubmed.ncbi.nlm.nih.gov/31231431
Publikováno v:
Computational Intelligence & Neuroscience. 4/28/2019, p1-25. 25p.
Publikováno v:
Proceedings of SPIE; 5/24/2022, Vol. 12176, p121760U-121760U-7, 1p
This book includes selected peer-reviewed papers presented at third International Conference on Computing and Communication Networks (ICCCN 2023), held at Manchester Metropolitan University, UK, during 17–18 November 2023. The book covers topics of
Autor:
Seyedali Mirjalili
Handbook of Whale Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides the most in-depth look at an emerging meta-heuristic that has been widely used in both science and industry. Whale Optimization Algorithm has been ci
Autor:
Endre Pap
This book is an up-to-date collection, in AI and environmental research, related to the project ATLAS. AI is used for gaining an understanding of complex research phenomena in the environmental sciences, encompassing heterogeneous, noisy, inaccurate,