Szczegóły publikacji
Opis bibliograficzny
Forecasting daily water consumption: a case study in Torun, Poland / Adam PIASECKI, Jakub JURASZ, Bartosz Kaźmierczak // Periodica Polytechnica. Civil Engineering ; ISSN 0553-6626. — 2018 — vol. 62 no. 3, s. 818–824. — Bibliogr. s. 823–824, Abstr.
Autorzy (3)
- AGHPiasecki Adam
- AGHJurasz Jakub
- Kaźmierczak Bartosz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 114216 |
|---|---|
| Data dodania do BaDAP | 2018-06-08 |
| Tekst źródłowy | URL |
| DOI | 10.3311/PPci.11930 |
| Rok publikacji | 2018 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Periodica Polytechnica, Civil Engineering |
Abstract
This paper presents Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) methods for predicting future daily water consumption values based on three antecedent records of water consumption and humidity forecast for a given day, which are considered as independent variables. Mean Absolute Percentage Error (MAPE) is obtained for different configurations of the input sets and of the ANN model structure. Additionally, sets of explanatory variables are enhanced with dummy variables indicating typical days: working day, Saturday, Sunday/public holidays. The results indicated the superiority of the ANN approach over MLR, although the observed difference in performance was very limited.
