Forecasting natural gas consumption in Istanbul using neural networks and multivariate time series methods
dc.contributor.author | Demirel, Ö. F. | |
dc.contributor.author | Zaim, S. | |
dc.contributor.author | Çalışkan, A. | |
dc.contributor.author | Özuyar, Pınar Gökçin | |
dc.date.accessioned | 2016-07-26T12:21:48Z | |
dc.date.available | 2016-07-26T12:21:48Z | |
dc.date.issued | 2012 | |
dc.identifier.issn | 1303-6203 | |
dc.identifier.uri | http://hdl.handle.net/10679/4290 | |
dc.identifier.uri | https://journals.tubitak.gov.tr/elektrik/abstract.htm?id=12919 | |
dc.description.abstract | The fast changes and developments in the world's economy have substantially increased energy consumption. Consequently, energy planning has become more critical and important. Forecasting is one of the main tools utilized in energy planning. Recently developed computational techniques such as genetic algorithms have led to easily produced and accurate forecasts. In this paper, a natural gas consumption forecasting methodology is developed and implemented with state-of-the-art techniques. We show that our forecasts are quite close to real consumption values. Accurate forecasting of natural gas consumption is extremely critical as the majority of purchasing agreements made are based on predictions. As a result, if the forecasts are not done correctly, either unused natural gas amounts must be paid or there will be shortages of natural gas in the planning periods. | |
dc.language.iso | eng | en_US |
dc.publisher | TÜBİTAK | |
dc.relation.ispartof | Turkish Journal of Electrical Engineering and Computer Sciences | |
dc.rights | openAccess | |
dc.title | Forecasting natural gas consumption in Istanbul using neural networks and multivariate time series methods | en_US |
dc.type | Article | en_US |
dc.peerreviewed | yes | |
dc.publicationstatus | published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0002-2505-2216 & YÖK ID 148993) Özuyar, Pınar | |
dc.contributor.ozuauthor | Özuyar, Pınar Gökçin | |
dc.identifier.volume | 20 | |
dc.identifier.issue | 5 | |
dc.identifier.startpage | 695 | |
dc.identifier.endpage | 711 | |
dc.identifier.wos | WOS:000306302000004 | |
dc.identifier.doi | 10.3906/elk-1101-1029 | |
dc.subject.keywords | Forecasting | |
dc.subject.keywords | Neural networks | |
dc.subject.keywords | Natural gas | |
dc.subject.keywords | Time series | |
dc.identifier.scopus | SCOPUS:2-s2.0-84861810597 | |
dc.contributor.authorFemale | 1 | |
dc.relation.publicationcategory | Article - International Refereed Journal - Institution Academic Staff |
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