Comparison of machine learning models in outdoor temperature sensing by commercial microwave link

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU145247" target="_blank" >RIV/00216305:26220/22:PU145247 - isvavai.cz</a>
Result on the web
<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_2_v3.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_2_v3.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Comparison of machine learning models in outdoor temperature sensing by commercial microwave link
Original language description
The main objective of this work is to focus on outdoor temperature prediction using machine learning based on parameters from commercial microwave links. This information can be used to refine the weather information at a given link location. Three machine learning models (random forest, linear regression, and lasso) are used for prediction using a combination of two datasets (ERA5 weather dataset and CML monitoring database dataset). The results were evaluated based on two evaluation metrics (R2 and mean absolute error (MAE)). In this work, the ERA5 outdoor temperature was found to be correlated with the temperature of the microwave link unit, and results were obtained with an accuracy of 0.87144 based on the MAE metric. Thus, the results can fairly well predict actual outdoor temperatures in the microwave link area based on the microwave link unit temperature.
Czech name
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Czech description
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Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings II of the 28th Conference STUDENT EEICT 2022 Selected Papers
ISBN
978-80-214-6030-0
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
318-322
Publisher name
Brno University of Technology, Faculty of Electrical Engineering and Communication
Place of publication
Brno
Event location
Brno
Event date
Apr 26, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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