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
A Phenotypic Learning Classifier System for Problems with C..:
, In:
Proceedings of the Genetic and Evolutionary Computation Conference
,
Liu, Yi
;
Cui, Yu
;
Cheng, Wen
... - p. 349-357 , 2024
Link:
https://dl.acm.org/doi/10.1145/3638529.3654007
RT T1
Proceedings of the Genetic and Evolutionary Computation Conference
: T1
A Phenotypic Learning Classifier System for Problems with Continuous Features
UL https://suche.suub.uni-bremen.de/peid=acm-3654007&Exemplar=1&LAN=DE A1 Liu, Yi A1 Cui, Yu A1 Cheng, Wen A1 Browne, Will Neil A1 Xue, Bing A1 Zhu, Chengyuan A1 Zhang, Yiding A1 Sheng, Mingkai A1 Zeng, Lingfang PB ACM YR 2024 K1 learning classifier system K1 mutation K1 absumption K1 subsumption K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Bio-inspired approaches K1 Genetic algorithms K1 Machine learning algorithms K1 Learning paradigms K1 Supervised learning K1 Supervised learning by regression SP 349 OP 357 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3638529.3654007 DO https://dl.acm.org/doi/10.1145/3638529.3654007 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)