Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Walid Atwa"'
Publikováno v:
PeerJ Computer Science, Vol 10, p e2067 (2024)
Accurate prediction of electricity generation from diverse renewable energy sources (RES) plays a pivotal role in optimizing power schedules within RES, contributing to the collective effort to combat climate change. While prior research often focuse
Externí odkaz:
https://doaj.org/article/a4303b86636a49a99ccfad5e052b1e98
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 10, Pp 10304-10318 (2022)
Energy saving is a major requirement in the design of routing algorithms to maximize the throughput and lifetime of wireless sensor networks. To address this requirement, this work proposes a routing algorithm based on a novel Reposition Particle Swa
Externí odkaz:
https://doaj.org/article/94af4eff2e794fdca5f411b2b936b901
Publikováno v:
ICT Express, Vol 8, Iss 2, Pp 276-282 (2022)
Most existing applications have a large number of evolving data streams. Clustering data streams is still a critical problem for these applications as the data are evolving and changes over time. Most existing algorithms are unsupervised learning in
Externí odkaz:
https://doaj.org/article/54f9db1ff18245ebafc8d0f70db32bc8
Autor:
Abdulwahab Ali Almazroi, Walid Atwa
Publikováno v:
Axioms, Vol 11, Iss 8, p 411 (2022)
The clustering method divides a dataset into groups with similar data using similarity metrics. However, discovering clusters in different densities, shapes and distinct sizes is still a challenging task. In this regard, experts and researchers opt t
Externí odkaz:
https://doaj.org/article/8bd0dca6aa5044648e17a899a604c604
Publikováno v:
ICT Express. 8:276-282
Most existing applications have a large number of evolving data streams. Clustering data streams is still a critical problem for these applications as the data are evolving and changes over time. Most existing algorithms are unsupervised learning in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::386aa2c6945ff1a91b960200dbcb7f47
https://doi.org/10.1016/j.icte.2021.08.017
https://doi.org/10.1016/j.icte.2021.08.017
Publikováno v:
IJCI. International Journal of Computers and Information. 8:77-81
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e953d44615694ba985f8a4ccdcc206b
https://doi.org/10.21608/ijci.2021.207757
https://doi.org/10.21608/ijci.2021.207757
Data management applications are rapidly growing applications that require more attention, especially in the big data era. Thus, it is critical to support these applications with novel and efficient algorithms that satisfy higher performance. Array d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18e2e142536995a51d39128c41ed6b6d
https://doi.org/10.21203/rs.3.rs-2388124/v1
https://doi.org/10.21203/rs.3.rs-2388124/v1
Publikováno v:
Scientific Programming, Vol 2021 (2021)
In this digital era of technology and software development tools, low-cost digital cameras and powerful video editing software (such as Adobe Premiere, Microsoft Movie Maker, and Magix Vegas) have become available for any common user. Through these s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9d3a7791c87c9020f50b55d67070e43
https://doi.org/10.1155/2021/5595850
https://doi.org/10.1155/2021/5595850
Publikováno v:
International Journal of Intelligent Systems and Applications. 13:58-68
Outlier detection is one of the important tasks in data mining. Detecting outliers over streaming data has become an important task in many applications, such as network analysis, fraud detections, and environment monitoring. One of the well-known ou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f877ed5a9cd97fd3476fccf6cb878326
https://doi.org/10.5815/ijisa.2021.01.05
https://doi.org/10.5815/ijisa.2021.01.05
Autor:
Abdulwahab Ali Almazroi, Walid Atwa
Publikováno v:
International Journal of Information Technology and Computer Science. 12:23-30
Semi.-supervised clustering algorithms aim to enhance the performance of clustering using the pairwise constraints. However, selecting these constraints randomly or improperly can minimize the performance of clustering in certain situations and with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f5b6949e00003a399a91aeb7265d7b6
https://doi.org/10.5815/ijitcs.2020.06.03
https://doi.org/10.5815/ijitcs.2020.06.03