Szczegóły publikacji
Opis bibliograficzny
Comparing the performance of regression and machine learning models in predicting the usable area of houses with multi-pitched roofs / Leszek Dawid, Anna BARAŃSKA, Paweł Baran // Applied Sciences (Basel) [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2076-3417. — 2025 — vol. 15 iss. 11 art. no. 6297, s. 1–23. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 21–23, Abstr. — Publikacja dostępna online od: 2025-06-03
Autorzy (3)
- Dawid Leszek
- AGHBarańska Anna
- Baran Paweł
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 160448 |
|---|---|
| Data dodania do BaDAP | 2025-06-18 |
| Tekst źródłowy | URL |
| DOI | 10.3390/app15116297 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Applied Sciences (Basel) |
Abstract
The usable floor area is one of the key parameters when appraising residential property. In Poland, valuers have to base their analysis on data from the Real Estate Price Register (RCN) in order to value a property. Unfortunately, these data often turn out to be incomplete, especially with regard to floor area, which makes the selection of reference properties difficult and can lead to erroneous valuation results. To address this problem, a study was conducted that used linear models, non-linear models and machine learning algorithms to calculate the floor area of buildings with complex multi-pitched roofs. The analysis was conducted using data sourced from the Database of Topographic Objects (BDOT10k). Three key factors were identified to provide a reliable estimate of usable floor area: the covered area, the height of the building and, optionally, the number of storeys. The results show that the linear model based on the design data achieved an accuracy of 88%, the non-linear model achieved 89% and the machine learning algorithms achieved 93%. For the existing building data from the city of Koszalin, the best model achieved an accuracy of 90%. The estimated values of the usable area of the building designs for the best model on the test set differed on average from the true ones by 8.7 m2, while for the existing buildings, the difference was 9.9 m2 on average (in both cases, the average relative error was about 7%).
