Electricity consumption forecasting using fuzzy time series

E. Bolturk; B. Oztaysi; I. U. Sari

doi:10.1109/CINTI.2012.6496768

Electricity consumption forecasting using fuzzy time series

E. Bolturk^*
, B. Oztaysi
, I. U. Sari

^*Bu çalışma için yazışmadan sorumlu yazar

Endüstri Mühendisliği Bölümü

Istanbul Ticaret University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

15 Atıf (Scopus)

Özet

Electricity is an important issue in energy management. Because of characteristic of electricity's non-storability, management of electricity is very valuable process. In this study, a Turkish company's two years electricity consumption have examined in order to predict possible electricity consumption. We used fuzzy time series with Singh's Method. Further, with the same data we compared total values of three periods (Unified consumption amount) and total consumption forecasts with their actuals. Finally we decide that which way is more accurate with root-mean-square deviation evaluation.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings
Sayfalar	245-249
Sayfa sayısı	5
DOI'lar	https://doi.org/10.1109/CINTI.2012.6496768
Yayın durumu	Yayınlandı - 2012
Etkinlik	13th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2012 - Budapest, Hungary Süre: 20 Kas 2012 → 22 Kas 2012

Yayın serisi

Adı	CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings

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???event.eventtypes.event.conference???	13th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2012
Ülke/Bölge	Hungary
Şehir	Budapest
Periyot	20/11/12 → 22/11/12

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 9 Sanayi, Yenilikçilik ve Altyapı

Belgeye Erişim

10.1109/CINTI.2012.6496768

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Bolturk, E., Oztaysi, B., & Sari, I. U. (2012). Electricity consumption forecasting using fuzzy time series. In CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings (pp. 245-249). Makale 6496768 (CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings). https://doi.org/10.1109/CINTI.2012.6496768

@inproceedings{d4664d1b8b784d959808fd437407d99b,

title = "Electricity consumption forecasting using fuzzy time series",

abstract = "Electricity is an important issue in energy management. Because of characteristic of electricity's non-storability, management of electricity is very valuable process. In this study, a Turkish company's two years electricity consumption have examined in order to predict possible electricity consumption. We used fuzzy time series with Singh's Method. Further, with the same data we compared total values of three periods (Unified consumption amount) and total consumption forecasts with their actuals. Finally we decide that which way is more accurate with root-mean-square deviation evaluation.",

keywords = "Electricity demand forecasting, deseasonalization, fuzzy time series",

author = "E. Bolturk and B. Oztaysi and Sari, \{I. U.\}",

year = "2012",

doi = "10.1109/CINTI.2012.6496768",

language = "English",

isbn = "9781467352062",

series = "CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings",

pages = "245--249",

booktitle = "CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings",

note = "13th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2012 ; Conference date: 20-11-2012 Through 22-11-2012",

}

Bolturk, E, Oztaysi, B & Sari, IU 2012, Electricity consumption forecasting using fuzzy time series. in CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings., 6496768, CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings, pp. 245-249, 13th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2012, Budapest, Hungary, 20/11/12. https://doi.org/10.1109/CINTI.2012.6496768

Electricity consumption forecasting using fuzzy time series. / Bolturk, E.; Oztaysi, B.; Sari, I. U.
CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings. 2012. p. 245-249 6496768 (CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

TY - GEN

T1 - Electricity consumption forecasting using fuzzy time series

AU - Bolturk, E.

AU - Oztaysi, B.

AU - Sari, I. U.

PY - 2012

Y1 - 2012

N2 - Electricity is an important issue in energy management. Because of characteristic of electricity's non-storability, management of electricity is very valuable process. In this study, a Turkish company's two years electricity consumption have examined in order to predict possible electricity consumption. We used fuzzy time series with Singh's Method. Further, with the same data we compared total values of three periods (Unified consumption amount) and total consumption forecasts with their actuals. Finally we decide that which way is more accurate with root-mean-square deviation evaluation.

AB - Electricity is an important issue in energy management. Because of characteristic of electricity's non-storability, management of electricity is very valuable process. In this study, a Turkish company's two years electricity consumption have examined in order to predict possible electricity consumption. We used fuzzy time series with Singh's Method. Further, with the same data we compared total values of three periods (Unified consumption amount) and total consumption forecasts with their actuals. Finally we decide that which way is more accurate with root-mean-square deviation evaluation.

KW - Electricity demand forecasting

KW - deseasonalization

KW - fuzzy time series

UR - https://www.scopus.com/pages/publications/84876938818

U2 - 10.1109/CINTI.2012.6496768

DO - 10.1109/CINTI.2012.6496768

M3 - Conference contribution

AN - SCOPUS:84876938818

SN - 9781467352062

T3 - CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings

SP - 245

EP - 249

BT - CINTI 2012 - 13th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings

T2 - 13th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2012

Y2 - 20 November 2012 through 22 November 2012

ER -

Electricity consumption forecasting using fuzzy time series

Özet

Yayın serisi

???event.eventtypes.event.conference???

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap