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
Using Multiobjective Evolutionary Algorithms to Understand ..:
, In:
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion
,
Vallejo, Marta
;
Cosgrove, Jeremy
;
Alty, Jane E.
... - p. 13-14 , 2016
Link:
https://dl.acm.org/doi/10.1145/2908961.2909026
RT T1
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion
: T1
Using Multiobjective Evolutionary Algorithms to Understand Parkinson's Disease
UL https://suche.suub.uni-bremen.de/peid=acm-2909026&Exemplar=1&LAN=DE A1 Vallejo, Marta A1 Cosgrove, Jeremy A1 Alty, Jane E. A1 Smith, Stephen L. A1 Corne, David W. A1 Lones, Michael A. PB ACM YR 2016 K1 multi-objective evolutionary algorithms K1 parkinson's disease K1 polynomial regression K1 predictive modelling K1 Applied computing K1 Life and medical sciences K1 Health informatics K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Bio-inspired approaches K1 Genetic algorithms SP 13 OP 14 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/2908961.2909026 DO https://dl.acm.org/doi/10.1145/2908961.2909026 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)