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A hybrid method for time series prediction using EMD and SVR

  • Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

15 Atıf (Scopus)

Özet

Forecasting in several areas such as stock price, electricity power consumption, tourist arrival rates or capacity planning allows us to give decisions for future events. The rising up or falling down of the values can support researchers, economists or investors while giving their important decisions. This study aims to forecast the directional movements of electricity load demands and evaluates the performance on 3 load datasets. In experimental results, the proposed Empirical Mode Decomposition (EMD) and Support Vector Regression (SVR) based hybrid method is compared with single SVR. It is observed that the proposed EMD-SVR method outperforms the single SVR performance on direction measurements including Direction Accuracy, Correct Up and Correct Down trends.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıISCCSP 2014 - 2014 6th International Symposium on Communications, Control and Signal Processing, Proceedings
YayınlayanIEEE Computer Society
Sayfalar566-569
Sayfa sayısı4
ISBN (Basılı)9781479928903
DOI'lar
Yayın durumuYayınlandı - 2014
Etkinlik6th International Symposium on Communications, Control and Signal Processing, ISCCSP 2014 - Athens, Greece
Süre: 21 May 201423 May 2014

Yayın serisi

AdıISCCSP 2014 - 2014 6th International Symposium on Communications, Control and Signal Processing, Proceedings

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???event.eventtypes.event.conference???6th International Symposium on Communications, Control and Signal Processing, ISCCSP 2014
Ülke/BölgeGreece
ŞehirAthens
Periyot21/05/1423/05/14

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