MAÜ GCRIS Standart veritabanının içerik oluşturulması ve kurulumu Research Ecosystems (https://www.researchecosystems.com) tarafından devam etmektedir. Bu süreçte gördüğünüz verilerde eksikler olabilir.
 

Turkey Long-Term Energy Consumption Prediction Using Whale Optimization Algorithm

dc.authorid0000-0003-3030-8690
dc.contributor.authorBabaoglu,Merve
dc.contributor.authorHaznedar,Bülent
dc.date.accessioned2023-12-14T10:33:35Z
dc.date.available2023-12-14T10:33:35Z
dc.date.issued2021
dc.departmentMAÜ, Meslek Yüksekokulları, Mardin Meslek Yüksekokulu, Bilgisayar Teknolojileri Bölümüen_US
dc.description.abstractEnergy is one of the most important topics for the sustainable development of countries. Due to the fact that the energy used can be depleted, it imports many energy sources, and environmental factors, it is of great importance for Turkey to predict how much energy needs may be in the future. In this study, whale optimization algorithm (BOA) was preferred from heuristic algorithms in order to be able to estimate Turkey's energy demand until 2040. In order to determine the performance of the whale optimization algorithm, the results were compared with the genetic algorithm (GA). All models are arranged linearly and squared and the result is obtained. Data for independent variables such as gross domestic product (GDP), population, imports and exports affecting energy demand were used between 1990 and 2019. Modeling of the past 30 years has been provided to calculate the accuracy of the results. After obtaining the most suitable model, calculations were made according to 4 different scenarios for the next 20 years.en_US
dc.description.citationM. Babaoğlu and B. Haznedar, "Turkey Long-Term Energy Consumption Prediction Using Whale Optimization Algorithm," 2021 29th Signal Processing and Communications Applications Conference (SIU), Istanbul, Turkey, 2021, pp. 1-4, doi: 10.1109/SIU53274.2021.9477889.en_US
dc.description.provenanceSubmitted by Merve Babaoğlu (mervebabaoglu@artuklu.edu.tr) on 2023-12-14T10:33:11Z No. of bitstreams: 1 BOA-Enerji-Tüketim-Tahmini.pdf: 451246 bytes, checksum: e467384e8602f1d042cd718187b178c9 (MD5)en
dc.description.provenanceApproved for entry into archive by Merve Babaoğlu (mervebabaoglu@artuklu.edu.tr) on 2023-12-14T10:33:35Z (GMT) No. of bitstreams: 1 BOA-Enerji-Tüketim-Tahmini.pdf: 451246 bytes, checksum: e467384e8602f1d042cd718187b178c9 (MD5)en
dc.description.provenanceMade available in DSpace on 2023-12-14T10:33:35Z (GMT). No. of bitstreams: 1 BOA-Enerji-Tüketim-Tahmini.pdf: 451246 bytes, checksum: e467384e8602f1d042cd718187b178c9 (MD5) Previous issue date: 19en
dc.identifier.doi10.1109/SIU53274.2021.9477889
dc.identifier.uri10.1109/SIU53274.2021.9477889
dc.identifier.urihttps://hdl.handle.net/20.500.12514/4694
dc.institutionauthorBabaoglu, Merve
dc.institutionauthorHaznedar, Bülent
dc.language.isotren_US
dc.publisherIEEE(Institute of Electrical and Electronics Engineers)en_US
dc.relation.ispartof2021 29th Signal Processing and Communications Applications Conference (SIU)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMathematical modelen_US
dc.subjectOptimizationen_US
dc.subjectSpiralsen_US
dc.subjectSignal processing algorithmsen_US
dc.subjectPrediction algorithmsen_US
dc.subjectEnergy consumptionen_US
dc.titleTurkey Long-Term Energy Consumption Prediction Using Whale Optimization Algorithmen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
BOA-Enerji-Tüketim-Tahmini.pdf
Size:
440.67 KB
Format:
Adobe Portable Document Format
Description:
Tam Metin/Full Text

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.44 KB
Format:
Item-specific license agreed upon to submission
Description: