Szczegóły publikacji
Opis bibliograficzny
Wykorzystanie wielowarstwowych sztucznych sieci neuronowych do średnioterminowego prognozowania poboru wody – studium przypadku — Application of multilayer perceptron artificial neural networks to mid-term water consumption forecasting – a case study / Adam Piasecki, Jakub JURASZ, Włodzimierz Marszelewski // Ochrona Środowiska / Polskie Zrzeszenie Inżynierów i Techników Sanitarnych. Oddział Dolnośląski ; ISSN 1230-6169. — 2016 — vol. 38 nr 2, s. 17–22. — Bibliogr. s. 21, Abstr. — A. Piasecki - afiliacja: Uniwersytet Mikołaja Kopernika w Toruniu
Autorzy (3)
- Piasecki Adam
- AGHJurasz Jakub
- Marszelewski Włodzimierz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 100045 |
|---|---|
| Data dodania do BaDAP | 2016-09-23 |
| Rok publikacji | 2016 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Ochrona Środowiska |
Abstract
Multilayer perceptron (MLP) artifi cial neural networks were employed to monthly water consumption forecasting. Research encompassed Czerniewice, one of the estates in Torun with a dedicated waterworks system (different from the other part of the town). Initially, nine exogenous variables describing meteorological, economic and social conditions were examined. The forecasting process revealed that implementation of all input variables correlating with water consumption did not lead to the highest quality forecasts. In terms of quality, the best result (evaluated based on MAPE criterion) was achieved for a model built on variables such as number of residents with access to waterworks, water rate, maximum temperature and humidity, and average income per inhabitant. It was demonstrated that the selection of input variables used for water consumption forecasting should be adjusted to local conditions. In the example considered, artifi cial neural networks proved useful in mid-term water consumption forecasting.
