Discrete Time Series Forecasting of Hive Weight, In-Hive Temperature, and Hive Entrance Traffic in Non-Invasive Monitoring of Managed Honey Bee Colonies: Part I.
ARIMA
FAIR datasets
artificial neural networks
autoregressive integrated moving average
convolutional neural networks
discrete time series forecasting
hive monitoring sensors
long short-term memory
precision apiculture
predictive hive monitoring
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
04 Oct 2024
04 Oct 2024
Historique:
received:
17
08
2024
revised:
29
09
2024
accepted:
29
09
2024
medline:
16
10
2024
pubmed:
16
10
2024
entrez:
16
10
2024
Statut:
epublish
Résumé
From June to October, 2022, we recorded the weight, the internal temperature, and the hive entrance video traffic of ten managed honey bee (
Identifiants
pubmed: 39409473
pii: s24196433
doi: 10.3390/s24196433
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : United States Department of Agriculture
ID : 2024-67013-42521