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İLERİ BESLEMELİ YAPAY SİNİR AĞLARI KULLANARAK HARMONİK TANIMA

HARMONIC DETECTION USING FEED FORWARD ARTIFICIAL NEURAL NETWORKS

Journal Name:

  • Sigma Mühendislik ve Fen Bilimleri Dergisi

Publication Year:

  • 2006

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
In this study, the method to apply the feed forward neural networks with two different numbers of hidden layers for harmonic detection process in active filter are described. We have simulated the distorted wave including 5th, 7th, 11th, 13th harmonics and used them for training of the neural networks. The distorted wave including up to 25th harmonics were prepared for testing of the neural networks. Feed forward neural networks have been used to recognize each harmonic. The results show that these neural networks are applicable to detect each harmonic effectively. The results of the neural network with two hidden layers are better than that of the other.
Abstract (Original Language): 
Bu çalışmada, aktif filtre işlemlerinde harmonikleri tanıma için iki farklı gizli katman ile ileri beslemeli yapay sinir ağları metodu tanımlanmıştır. Distorsiyonlu dalga içerisinden 5.,7.,11. ve 13. harmoniklerin simülasyonu yapıldı ve bunlar sinir ağlarının eğitimi için kullanıldı. Sinir ağının testi için distorsiyonlu dalga içerisinden 25. harmoniğe kadar hazırlandı. İleri beslemeli sinir ağları harmoniklerin her birini tanımak için kullanılmıştır. Sonuçlar yapay sinir ağlarının harmonikleri tanımada etkili bir şekilde kullanılabileceğini göstermektedir. Sonuc olarak iki gizli katmanlı sinir ağı diğerinden daha iyidir.
FULL TEXT (PDF): 
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REFERENCES

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