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Naslov:Micro-location temperature prediction leveraging deep learning approaches
Avtorji:ID Krepek, Amadej (Avtor)
ID Fister, Iztok (Avtor)
ID Fister, Iztok (Avtor)
Datoteke:.pdf applsci-15-06793_(1).pdf (8,81 MB)
MD5: E8BF92492695F3A33C7496BD1896D733
 
Jezik:Angleški jezik
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
Opis:Nowadays, technological progress has promoted the integration of artificial intelligence into modern human lives rapidly. On the other hand, extreme weather events in recent years have started to influence human well-being. As a result, these events have been addressed by artificial intelligence methods more and more frequently. In line with this, the paper focuses on searching for predicting the air temperature in a particular Slovenian micro-location by using a weather prediction model Maximus based on a longshort term memory neural network learned by the long-term, lower-resolution dataset CERRA. During this huge experimental study, the Maximus prediction model was tested with the ICON-D2 general-purpose weather prediction model and validated with real data from the mobile weather station positioned at a specific micro-location. The weather station employs Internet of Things sensors for measuring temperature, humidity, wind speed and direction, and rain, while it is powered by solar cells. The results of comparing the Maximus proposed prediction model for predicting the air temperature in micro-locations with the general-purpose weather prediction model ICON-D2 has encouraged the authors to continue searching for an air temperature prediction model at the micro-location in the future.
Ključne besede:long short-term memory neural networks, air temperature, micro-location, prediction, weather, Internet of Things
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:13.05.2025
Datum sprejetja članka:13.06.2025
Datum objave:17.06.2025
Založnik:MDPI
Leto izida:2025
Št. strani:26 str.
Številčenje:Vol. 15, iss. 12, [article no.] 6793
PID:20.500.12556/DKUM-95549 Novo okno
UDK:004.8
COBISS.SI-ID:249547011 Novo okno
DOI:10.3390/app15126793 Novo okno
ISSN pri članku:2076-3417
Avtorske pravice:© 2025 by the authors
Datum objave v DKUM:25.09.2025
Število ogledov:158
Število prenosov:13
Metapodatki:XML DC-XML DC-RDF
Področja:Ostalo
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Skupna ocena:(0 glasov)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
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Gradivo je del revije

Naslov:Applied sciences
Skrajšan naslov:Appl. sci.
Založnik:MDPI
ISSN:2076-3417
COBISS.SI-ID:522979353 Novo okno

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:nevronske mreže, temperatura zraka, mikro lokacije, vreme, internet stvari


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