Forecast Combination by Using Artificial Neural Networks

ALADAĞ Ç. H., Egrioglu E., Yolcu U.

NEURAL PROCESSING LETTERS, cilt.32, sa.3, ss.269-276, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 3
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1007/s11063-010-9156-7
  • Dergi Adı: NEURAL PROCESSING LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.269-276
  • Anahtar Kelimeler: Artificial neural networks, Forecast combination, Forecasting, Fuzzy time series, FUZZY TIME-SERIES, ENROLLMENTS, MODEL
  • Marmara Üniversitesi Adresli: Hayır

Özet

One of the efficient ways for obtaining accurate forecasts is usage of forecast combination method. This approach consists of combining different forecast values obtained from different forecasting models. Also artificial neural networks and fuzzy time series approaches have proved their success in the field of forecasting. In this study, a new forecast combination approach based on artificial neural networks is proposed. The forecasts obtain from different fuzzy time series models are combined by utilizing artificial neural networks. The proposed method is applied to index of Istanbul stock exchange (IMKB) time series and the results are compared to other forecast combination methods available in the literature. As a result of the implementation, it is seen that the proposed forecast combination approach produces better forecasts than those produced by other methods.