A Novel Harmony Search Based Method for Noise Minimization on EEG Signals EEG Sinyallerinde Gürültü Minimizasyonu için Harmoni Arama Temelli Yeni Bir Yöntem

Celil S., ASLAN S., Demirci S.

6th International Conference on Computer Science and Engineering, UBMK 2021, Ankara, Türkiye, 15 - 17 Eylül 2021, ss.747-750 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/ubmk52708.2021.9559025
  • Basıldığı Şehir: Ankara
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.747-750
  • Anahtar Kelimeler: Big data optimization, EEG, Harmony search algorithm, SlinkHSA
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Big data is a topic that is increasing in popularity day by day, and new techniques are being developed for the optimization processes performed on it. Harmony Search (HS) algorithm, inspired by music and harmonies, is an intuitive algorithm and has been used for the optimization of many problems. In this study, a new technique called source-linked HS algorithm (slinkHSA) focusing on big data optimization problems is presented. Experimental results were obtained with the slinkHS algorithm, results were compared with other popular metaheuristic algorithms and unmodified HS algorithm. The obtained results showed that the technique applied in the slinkHS algorithm adapted to the problem better, in this way better results could be obtained than other algorithms compared.