Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Attia Qammar"'
Publikováno v:
Energies, Vol 15, Iss 18, p 6799 (2022)
Smart Grids (SGs) are governed by advanced computing, control technologies, and networking infrastructure. However, compromised cybersecurity of the smart grid not only affects the security of existing energy systems but also directly impacts nationa
Externí odkaz:
https://doaj.org/article/b20a4f5d8e8a4886bc26ce73e697128f
Publikováno v:
Artificial Intelligence Review. 56:3951-3985
Federated learning (FL) is a promising framework for distributed machine learning that trains models without sharing local data while protecting privacy. FL exploits the concept of collaborative learning and builds privacy-preserving models. Neverthe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::036a4b64e9acd2bd968ae16e0951aa9c
https://doi.org/10.1007/s10462-022-10271-9
https://doi.org/10.1007/s10462-022-10271-9
Publikováno v:
Computer Systems Science and Engineering. 43:915-930
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a87cb8b863477b794764da0056bae5e2
https://doi.org/10.32604/csse.2022.023652
https://doi.org/10.32604/csse.2022.023652
Publikováno v:
Energies; Volume 15; Issue 18; Pages: 6799
Smart Grids (SGs) are governed by advanced computing, control technologies, and networking infrastructure. However, compromised cybersecurity of the smart grid not only affects the security of existing energy systems but also directly impacts nationa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::334e1a34d53c81fed73baae7706a6634
Federated learning (FL) has received a great deal of research attention in the context of privacy protection restrictions. By jointly training deep learning models, a variety of training tasks can be competently performed with the help of invited par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::092c5b0fb72b701c9f832eda3897cd26
http://urn.kb.se/resolve?urn=urn:nbn:se:bth-22394
http://urn.kb.se/resolve?urn=urn:nbn:se:bth-22394
