I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Swarm Based Algorithms for Neural Network Training:
, In:
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
,
McLean, Reginald
;
Ombuki-Berman, Beatrice
;
Engelbrecht, Andries P.
- p. 2585-2592 , 2020
Link:
https://doi.org/10.1109/SMC42975.2020.9283242
RT T1
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
: T1
Swarm Based Algorithms for Neural Network Training
UL https://suche.suub.uni-bremen.de/peid=ieee-9283242&Exemplar=1&LAN=DE A1 McLean, Reginald A1 Ombuki-Berman, Beatrice A1 Engelbrecht, Andries P. YR 2020 SN 2577-1655 K1 Training K1 Frequency selective surfaces K1 Microorganisms K1 Artificial neural networks K1 Classification algorithms K1 Particle swarm optimization K1 Optimization SP 2585 OP 2592 LK http://dx.doi.org/https://doi.org/10.1109/SMC42975.2020.9283242 DO https://doi.org/10.1109/SMC42975.2020.9283242 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)