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 machine learning algorithm-based approach (MaxEnt) for pr..:
Aidoo, Owusu Fordjour
;
Souza, Philipe Guilherme Corcino
;
da Silva, Ricardo Siqueira
...
Ecological Informatics. 71 (2022) - p. 101792 , 2022
Link:
https://doi.org/10.1016/j.ecoinf.2022.101792
RT Journal T1
A machine learning algorithm-based approach (MaxEnt) for predicting invasive potential of Trioza erytreae on a global scale
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.ecoinf.2022.101792&Exemplar=1&LAN=DE A1 Aidoo, Owusu Fordjour A1 Souza, Philipe Guilherme Corcino A1 da Silva, Ricardo Siqueira A1 Júnior, Paulo Antonio Santana A1 Picanço, Marcelo Coutinho A1 Osei-Owusu, Jonathan A1 Sétamou, Mamoudou A1 Ekesi, Sunday A1 Borgemeister, Christian PB Elsevier BV YR 2022 SN 1574-9541 JF Ecological Informatics VO 71 SP 101792 LK http://dx.doi.org/https://doi.org/10.1016/j.ecoinf.2022.101792 DO https://doi.org/10.1016/j.ecoinf.2022.101792 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)