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Fuzzy neural tree for knowledge driven design

  • Ö Ciftcioglu*
  • , M. S. Bittermann
  • , I. S. Sariyildiz
  • *Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

2 Atıf (Scopus)

Özet

A neural tree structure is considered with nodes of neuronal type, which is a Gaussian function playing the role of membership function. The total tree structure effectively works as a fuzzy logic model with inputs and outputs. In this model the locations of the fuzzy membership functions are normalized to unity so that the system has several desirable features and it represents a fuzzy model maintaining the transparency and effectiveness while dealing with complexity. The research is described in detail and its outstanding merits are pointed out in a framework having transparent fuzzy modelling properties and addressing complexity issues at the same time. A demonstrative application exercise of the model is presented and the favourable performance is demonstrated.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıSecond International Conference on Innovative Computing, Information and Control, ICICIC 2007
YayınlayanIEEE Computer Society
Sayfalar277-280
Sayfa sayısı4
ISBN (Basılı)0769528821, 9780769528823
DOI'lar
Yayın durumuYayınlandı - 2007
Harici olarak yayınlandıEvet
Etkinlik2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 - Kumamoto, Japan
Süre: 5 Eyl 20077 Eyl 2007

Yayın serisi

AdıSecond International Conference on Innovative Computing, Information and Control, ICICIC 2007

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???event.eventtypes.event.conference???2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007
Ülke/BölgeJapan
ŞehirKumamoto
Periyot5/09/077/09/07

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