Pregled bibliografske jedinice broj: 431716
Predicting natural gas consumption by neural networks
Predicting natural gas consumption by neural networks // Tehnički vjesnik, 16 (2009), 3; 51-61 (podatak o recenziji nije dostupan, prethodno priopćenje, znanstveni)
CROSBI ID: 431716 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Predicting natural gas consumption by neural networks
Autori
Tonković, Zlatko ; Zekić-Sušac, Marijana ; Somolanji, Marija
Izvornik
Tehnički vjesnik (1330-3651) 16
(2009), 3;
51-61
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, prethodno priopćenje, znanstveni
Ključne riječi
natural gas consumption; neural networks; multilayer perceptron; radial basic function network; fuzzy variable
Sažetak
The aim of the paper is to create a prediction model of natural consumtpion on a regioanal level by using neural networks, and to analyze the results in order to improve prediction accuracy in further research. The outputvariable consisted of the next-day gas consuption in hourly intervals, while the input space included previous-day consumption in addition to exogenus variables. After conducting a feature selection procedure, two neural network algorithams were trained and tested: the multilayer perceptron and the radial basis function network with different activation functions. The dataset consisted of real historical data of Croatian gas distributor. The best neural network model is selected on the basis of the mean absolute percentage error obtained on the test sample. The results were analyzed, and some critical hours and days were identified. Gudidelines were reported that could be valuable to both researchers and practitioners in this area.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Projekti:
010-0101195-1048 - Modeli za ocjenu rizičnosti poslovanja poduzeća (Šarlija, Nataša, MZOS ) ( CroRIS)
152-1521473-1474 - Napredni postupci izravne izradbe polimernih proizvoda (Raos, Pero, MZOS ) ( CroRIS)
Ustanove:
Ekonomski fakultet, Osijek,
Strojarski fakultet, Slavonski Brod
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
Uključenost u ostale bibliografske baze podataka::
- Compendex (EI Village)
- INSPEC
- Scopus, Geo Abstract, CSA