Results

eNauka >  Results >  Tackling IoT Security Challenge by Metaheuristics Tuned Extreme Learning Machine
Title: Tackling IoT Security Challenge by Metaheuristics Tuned Extreme Learning Machine
Authors: L. Jovanovic; M. Gajevic; M. Dobrojevic  ; N. Budimirovic; N. Bacanin  ; M. Zivkovic  
Issue Date: 2023
Publication: LNNS Lecture Notes in Networks and Systems: ICoISS 2023: International Conference on Intelligent Sustainable Systems, volume 665
Publisher: Springer, Singapore
Type: Book parts
Collation: str. 507-522
DOI: 10.1007/978-981-99-1726-6_39
Scopus-ID: 2-s2.0-85166901970
URI: https://link.springer.com/chapter/10.1007/978-981-99-1726-6_39
http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/3/9508
https://enauka.gov.rs/handle/123456789/764373
URL: https://link.springer.com/chapter/10.1007/978-981-99-1726-6_39
M-category: 
Mp. category will be shown later

13
SCOPUSTM
Altmetric
Dimensions
Unpaywall

Google ScholarTM

Items in eNauka are protected by copyright, with all rights reserved, unless otherwise indicated.