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
Applicability of Machine-Learned Regression Models to Estim..:
Uk-Hyeon Yeo
;
Seng-Kyoun Jo
;
Se-Han Kim
...
Precision and Digital Agriculture. , 2023
Link:
https://doi.org/10.3390/agronomy13020328
RT Journal T1
Applicability of Machine-Learned Regression Models to Estimate Internal Air Temperature and CO2 Concentration of a Pig House
UL https://suche.suub.uni-bremen.de/peid=base-ftmdpi:oai:mdpi.com:_2073-4395_13_2_328_&Exemplar=1&LAN=DE A1 Uk-Hyeon Yeo A1 Seng-Kyoun Jo A1 Se-Han Kim A1 Dae-Heon Park A1 Deuk-Young Jeong A1 Se-Jun Park A1 Hakjong Shin A1 Rack-Woo Kim PB Multidisciplinary Digital Publishing Institute YR 2023 K1 air temperature K1 carbon dioxide K1 machine learning K1 pig house K1 regression model JF Precision and Digital Agriculture LK http://dx.doi.org/https://doi.org/10.3390/agronomy13020328 DO https://doi.org/10.3390/agronomy13020328 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)