Preliminary communication

https://doi.org/10.17559/TV-20190822153751

Prediction of Energy Consumption in Buildings Using Support Vector Machine

Todorka Samardzioska* ; Ss. Cyril and Methodius University in Skopje, Faculty of Civil Engineering, 24, Partizanski Odrediblvd, Skopje, Macedonia
Valentina Zileska Pancovska ; Ss. Cyril and Methodius University in Skopje, Faculty of Civil Engineering, 24, Partizanski Odrediblvd, Skopje, Macedonia
Silvana Petrusheva ; Ss. Cyril and Methodius University in Skopje, Faculty of Civil Engineering, 24, Partizanski Odrediblvd, Skopje, Macedonia
Blagica Sekovska ; Ss. Cyril and Methodius University in Skopje, Faculty of Veterinary Medicine, St. "Lazar Pop-Trajkov" 5-7, Skopje, Macedonia

Abstract

The energy consumption of buildings can directly affect the buildings users' budget and their satisfaction with the investment in the property. Vice versa, buildings energy consumption has a social implication on the buildings' users. Additionally, building energy consumption is connected with the buildings influence on the environment due to the CO2 emission. Thus, having a model for energy usage prediction is of crucial importance. Data for sixty real-built buildings were collected. Using support vector machine, a model was developed for prediction of energy consumption. The mean absolute percentage error of the model is 2,44% and the coefficient of determination of the model R2 is 94,72%, which expresses the global fit of the model. The model is useful for all participants in the designs of buildings, particularly in the early phases. It can serve as a decision support model during the process of selection of optimal building design.

Keywords

buildings; energy consumption; energy efficiency, prediction; support vector machine

Hrčak ID:

255882

URI

https://hrcak.srce.hr/255882

Publication date:

17.4.2021.

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