A fuzzy neural tree based on likelihood

Ozer Ciftcioglu; Michael S. Bittermann

doi:10.1109/FUZZ-IEEE.2015.7337971

A fuzzy neural tree based on likelihood

Ozer Ciftcioglu
, Michael S. Bittermann

Delft University of Technology
Maltepe University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

6 Atıf (Scopus)

Özet

A novel type of fuzzy neural system is presented. It involves the neural tree concept and is termed as fuzzy neural tree (FNT). Each tree node uses a Gaussian as a fuzzy membership function so that the approach uniquely is in align with both the probabilistic and possibilistic interpretations of fuzzy membership, thereby presenting a novel type of network. The tree is structured by the domain knowledge and parameterized by likelihood. The FNT is described in detail pointing out its various potential utilizations, in which complex modeling and multi-objective optimization are demanded. One of such utilizations concerns design. This is exemplified and its effectiveness is demonstrated by computer experiments in the realm of Architectural design.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems
Editörler	Adnan Yazici, Nikhil R. Pal, Uzay Kaymak, Trevor Martin, Hisao Ishibuchi, Chin-Teng Lin, Joao M. C. Sousa, Bulent Tutmez
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9781467374286
DOI'lar	https://doi.org/10.1109/FUZZ-IEEE.2015.7337971
Yayın durumu	Yayınlandı - 25 Kas 2015
Harici olarak yayınlandı	Evet
Etkinlik	2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 - Istanbul, Türkiye Süre: 2 Ağu 2015 → 5 Ağu 2015

Yayın serisi

Adı	IEEE International Conference on Fuzzy Systems
Hacim	2015-November
ISSN (Basılı)	1098-7584

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???event.eventtypes.event.conference???	2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015
Ülke/Bölge	Türkiye
Şehir	Istanbul
Periyot	2/08/15 → 5/08/15

Bibliyografik not

Publisher Copyright:
© 2015 IEEE.

Belgeye Erişim

10.1109/FUZZ-IEEE.2015.7337971

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Ciftcioglu, O., & Bittermann, M. S. (2015). A fuzzy neural tree based on likelihood. In A. Yazici, N. R. Pal, U. Kaymak, T. Martin, H. Ishibuchi, C.-T. Lin, J. M. C. Sousa, & B. Tutmez (Eds.), FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems Makale 7337971 (IEEE International Conference on Fuzzy Systems; Hac. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2015.7337971

Ciftcioglu, Ozer ; Bittermann, Michael S. / A fuzzy neural tree based on likelihood. FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems. editör / Adnan Yazici ; Nikhil R. Pal ; Uzay Kaymak ; Trevor Martin ; Hisao Ishibuchi ; Chin-Teng Lin ; Joao M. C. Sousa ; Bulent Tutmez. Institute of Electrical and Electronics Engineers Inc., 2015. (IEEE International Conference on Fuzzy Systems).

@inproceedings{d8c4e732a6224d4b837ac68e6c7fceaa,

title = "A fuzzy neural tree based on likelihood",

abstract = "A novel type of fuzzy neural system is presented. It involves the neural tree concept and is termed as fuzzy neural tree (FNT). Each tree node uses a Gaussian as a fuzzy membership function so that the approach uniquely is in align with both the probabilistic and possibilistic interpretations of fuzzy membership, thereby presenting a novel type of network. The tree is structured by the domain knowledge and parameterized by likelihood. The FNT is described in detail pointing out its various potential utilizations, in which complex modeling and multi-objective optimization are demanded. One of such utilizations concerns design. This is exemplified and its effectiveness is demonstrated by computer experiments in the realm of Architectural design.",

keywords = "Fuzzy logic, evolutionary computation, knowledge modeling, likelihood, neural tree, probability possibility",

author = "Ozer Ciftcioglu and Bittermann, \{Michael S.\}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 ; Conference date: 02-08-2015 Through 05-08-2015",

year = "2015",

month = nov,

day = "25",

doi = "10.1109/FUZZ-IEEE.2015.7337971",

language = "English",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Adnan Yazici and Pal, \{Nikhil R.\} and Uzay Kaymak and Trevor Martin and Hisao Ishibuchi and Chin-Teng Lin and Sousa, \{Joao M. C.\} and Bulent Tutmez",

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Ciftcioglu, O & Bittermann, MS 2015, A fuzzy neural tree based on likelihood. in A Yazici, NR Pal, U Kaymak, T Martin, H Ishibuchi, C-T Lin, JMC Sousa & B Tutmez (eds), FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems., 7337971, IEEE International Conference on Fuzzy Systems, hac. 2015-November, Institute of Electrical and Electronics Engineers Inc., 2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015, Istanbul, Türkiye, 2/08/15. https://doi.org/10.1109/FUZZ-IEEE.2015.7337971

A fuzzy neural tree based on likelihood. / Ciftcioglu, Ozer; Bittermann, Michael S.
FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems. ed. / Adnan Yazici; Nikhil R. Pal; Uzay Kaymak; Trevor Martin; Hisao Ishibuchi; Chin-Teng Lin; Joao M. C. Sousa; Bulent Tutmez. Institute of Electrical and Electronics Engineers Inc., 2015. 7337971 (IEEE International Conference on Fuzzy Systems; Hac. 2015-November).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - A fuzzy neural tree based on likelihood

AU - Ciftcioglu, Ozer

AU - Bittermann, Michael S.

PY - 2015/11/25

Y1 - 2015/11/25

N2 - A novel type of fuzzy neural system is presented. It involves the neural tree concept and is termed as fuzzy neural tree (FNT). Each tree node uses a Gaussian as a fuzzy membership function so that the approach uniquely is in align with both the probabilistic and possibilistic interpretations of fuzzy membership, thereby presenting a novel type of network. The tree is structured by the domain knowledge and parameterized by likelihood. The FNT is described in detail pointing out its various potential utilizations, in which complex modeling and multi-objective optimization are demanded. One of such utilizations concerns design. This is exemplified and its effectiveness is demonstrated by computer experiments in the realm of Architectural design.

AB - A novel type of fuzzy neural system is presented. It involves the neural tree concept and is termed as fuzzy neural tree (FNT). Each tree node uses a Gaussian as a fuzzy membership function so that the approach uniquely is in align with both the probabilistic and possibilistic interpretations of fuzzy membership, thereby presenting a novel type of network. The tree is structured by the domain knowledge and parameterized by likelihood. The FNT is described in detail pointing out its various potential utilizations, in which complex modeling and multi-objective optimization are demanded. One of such utilizations concerns design. This is exemplified and its effectiveness is demonstrated by computer experiments in the realm of Architectural design.

KW - Fuzzy logic

KW - evolutionary computation

KW - knowledge modeling

KW - likelihood

KW - neural tree

KW - probability possibility

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U2 - 10.1109/FUZZ-IEEE.2015.7337971

DO - 10.1109/FUZZ-IEEE.2015.7337971

M3 - Conference contribution

AN - SCOPUS:84975780063

T3 - IEEE International Conference on Fuzzy Systems

BT - FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems

A2 - Yazici, Adnan

A2 - Pal, Nikhil R.

A2 - Kaymak, Uzay

A2 - Martin, Trevor

A2 - Ishibuchi, Hisao

A2 - Lin, Chin-Teng

A2 - Sousa, Joao M. C.

A2 - Tutmez, Bulent

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015

Y2 - 2 August 2015 through 5 August 2015

ER -

Ciftcioglu O, Bittermann MS. A fuzzy neural tree based on likelihood. In Yazici A, Pal NR, Kaymak U, Martin T, Ishibuchi H, Lin CT, Sousa JMC, Tutmez B, editörler, FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers Inc. 2015. 7337971. (IEEE International Conference on Fuzzy Systems). doi: 10.1109/FUZZ-IEEE.2015.7337971

A fuzzy neural tree based on likelihood

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Yayın serisi

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Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

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