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Scientific paper - Original scientific paper
Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia
Energy reports, 12 (2024); 3595-3606. https://doi.org/10.1016/j.egyr.2024.09.039
Begić Juričić, Hana; Krstić, Hrvoje

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Begić Juričić, H. & Krstić, H. (2024). Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia. Energy reports, 12., 3595-3606. doi: 10.1016/j.egyr.2024.09.039

Begić Juričić, Hana and Hrvoje Krstić. "Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia." Energy reports, vol. 12, 2024, pp. 3595-3606. https://doi.org/10.1016/j.egyr.2024.09.039

Begić Juričić, Hana and Hrvoje Krstić. "Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia." Energy reports 12 (2024): 3595-3606. https://doi.org/10.1016/j.egyr.2024.09.039

Begić Juričić, H. and Krstić, H. (2024) 'Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia', Energy reports, 12, pp. 3595-3606. doi: 10.1016/j.egyr.2024.09.039

Begić Juričić H, Krstić H. Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia. Energy reports [Internet]. 2024 [cited 2025 February 04];12:3595-3606. doi: 10.1016/j.egyr.2024.09.039

H. Begić Juričić and H. Krstić, "Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia", Energy reports, vol. 12, pp. 3595-3606, 2024. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:133:937757. [Accessed: 04 February 2025]

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Metadata
Title (english)Comparing MLR and ANN models for school building electrical energy prediction in Osijek-Baranja County in Croatia
AuthorHana Begić Juričić
AuthorHrvoje Krstić
Author's institutionJosip Juraj Strossmayer University of Osijek
Faculty of Civil Engineering and Architecture Osijek
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Civil Engineering
Abstract (english)
This paper presents a study conducted in Osijek-Baranja County, Croatia, to predict electrical energy consumption in school buildings. Data from the Energy Management Information System (EMIS) database for primary and secondary schools were analyzed using Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). The ANN model achieved a high R² of 0957 in the training set, with lower Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) than the MLR model, which had an R² of 0950. On the validation set, the ANN model maintained an R² of 0954 and showed slightly better performance with a lower Coefficient of Variation of RMSE (CVRMSE) of 19,79 %, compared to the MLR model’s CVRMSE of 20,50 %. These results indicate that the ANN model generally provides more accurate and reliable predictions for energy consumption in school buildings. However, both models provided a robust positive correlation between the predicted and actual values.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleEnergy reports
Numberingvol. 12, pp. 3595-3606
e-ISSN2352-4847
DOIhttps://doi.org/10.1016/j.egyr.2024.09.039
URN:NBNurn:nbn:hr:133:937757
Publication2024
Document URLhttps://www.sciencedirect.com/science/article/pii/S2352484724006152
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) icon
Created on2025-02-04 08:47:26