IBitABC: Lokal Arama ile Genişletilmiş İkili Yapay Ar Kolonisi Algoritmasi

Zeynep Banu Özger; Bülent Bolat; Banu Diri

doi:10.1109/UBMK.2017.8093589

IBitABC: Lokal Arama ile Genişletilmiş İkili Yapay Ar Kolonisi Algoritmasi

Zeynep Banu Özger
, Bülent Bolat
, Banu Diri

Yildiz Technical University

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

Özet

Feature selection is a process of selecting a subset of features that is highly distinguishable from the data set to obtain better or at least equivalent success rates. Artificial Bee Colony (ABC) Algorithm is a intelligence algorithm that model the behavior of honey bees in the nature of food seeking behavior and has been developed to produce a solution at continuous space. BitABC is a bitwise operator based binary ABC algorithm that can produce fast results in binary space. In this study, BitABC was improved to increase the local search capacity and adapted to the feature selection problem to measure the success of the proposed method. The results obtained using 10 data sets from UCI Machine Learning Repository indicate the success of the proposed method.

Tercüme edilen katkı başlığı	IBitABC: Improved binary artificial bee colony algorithm with local search
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	2nd International Conference on Computer Science and Engineering, UBMK 2017
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	165-170
Sayfa sayısı	6
ISBN (Elektronik)	9781538609309
DOI'lar	https://doi.org/10.1109/UBMK.2017.8093589
Yayın durumu	Yayınlandı - 31 Eki 2017
Harici olarak yayınlandı	Evet
Etkinlik	2nd International Conference on Computer Science and Engineering, UBMK 2017 - Antalya, Türkiye Süre: 5 Eki 2017 → 8 Eki 2017

Yayın serisi

Adı	2nd International Conference on Computer Science and Engineering, UBMK 2017

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2nd International Conference on Computer Science and Engineering, UBMK 2017
Ülke/Bölge	Türkiye
Şehir	Antalya
Periyot	5/10/17 → 8/10/17

Bibliyografik not

Publisher Copyright:
© 2017 IEEE.

Keywords

Artificial Bee Colony
Classification
Feature selection
Optimization

Belgeye Erişim

10.1109/UBMK.2017.8093589

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Özger, Z. B., Bolat, B., & Diri, B. (2017). IBitABC: Lokal Arama ile Genişletilmiş İkili Yapay Ar Kolonisi Algoritmasi. In 2nd International Conference on Computer Science and Engineering, UBMK 2017 (pp. 165-170). Makale 8093589 (2nd International Conference on Computer Science and Engineering, UBMK 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UBMK.2017.8093589

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title = "IBitABC: Lokal Arama ile Geni{\c s}letilmi{\c s} İkili Yapay Ar Kolonisi Algoritmasi",

abstract = "Feature selection is a process of selecting a subset of features that is highly distinguishable from the data set to obtain better or at least equivalent success rates. Artificial Bee Colony (ABC) Algorithm is a intelligence algorithm that model the behavior of honey bees in the nature of food seeking behavior and has been developed to produce a solution at continuous space. BitABC is a bitwise operator based binary ABC algorithm that can produce fast results in binary space. In this study, BitABC was improved to increase the local search capacity and adapted to the feature selection problem to measure the success of the proposed method. The results obtained using 10 data sets from UCI Machine Learning Repository indicate the success of the proposed method.",

keywords = "Artificial Bee Colony, Classification, Feature selection, Optimization",

author = "{\"O}zger, \{Zeynep Banu\} and B{\"u}lent Bolat and Banu Diri",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2nd International Conference on Computer Science and Engineering, UBMK 2017 ; Conference date: 05-10-2017 Through 08-10-2017",

year = "2017",

month = oct,

day = "31",

doi = "10.1109/UBMK.2017.8093589",

language = "T{\"u}rk{\c c}e",

series = "2nd International Conference on Computer Science and Engineering, UBMK 2017",

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

pages = "165--170",

booktitle = "2nd International Conference on Computer Science and Engineering, UBMK 2017",

address = "United States",

}

Özger, ZB, Bolat, B & Diri, B 2017, IBitABC: Lokal Arama ile Genişletilmiş İkili Yapay Ar Kolonisi Algoritmasi. in 2nd International Conference on Computer Science and Engineering, UBMK 2017., 8093589, 2nd International Conference on Computer Science and Engineering, UBMK 2017, Institute of Electrical and Electronics Engineers Inc., pp. 165-170, 2nd International Conference on Computer Science and Engineering, UBMK 2017, Antalya, Türkiye, 5/10/17. https://doi.org/10.1109/UBMK.2017.8093589

IBitABC: Lokal Arama ile Genişletilmiş İkili Yapay Ar Kolonisi Algoritmasi. / Özger, Zeynep Banu; Bolat, Bülent; Diri, Banu.
2nd International Conference on Computer Science and Engineering, UBMK 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 165-170 8093589 (2nd International Conference on Computer Science and Engineering, UBMK 2017).

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

TY - GEN

T1 - IBitABC

T2 - 2nd International Conference on Computer Science and Engineering, UBMK 2017

AU - Özger, Zeynep Banu

AU - Bolat, Bülent

AU - Diri, Banu

PY - 2017/10/31

Y1 - 2017/10/31

N2 - Feature selection is a process of selecting a subset of features that is highly distinguishable from the data set to obtain better or at least equivalent success rates. Artificial Bee Colony (ABC) Algorithm is a intelligence algorithm that model the behavior of honey bees in the nature of food seeking behavior and has been developed to produce a solution at continuous space. BitABC is a bitwise operator based binary ABC algorithm that can produce fast results in binary space. In this study, BitABC was improved to increase the local search capacity and adapted to the feature selection problem to measure the success of the proposed method. The results obtained using 10 data sets from UCI Machine Learning Repository indicate the success of the proposed method.

AB - Feature selection is a process of selecting a subset of features that is highly distinguishable from the data set to obtain better or at least equivalent success rates. Artificial Bee Colony (ABC) Algorithm is a intelligence algorithm that model the behavior of honey bees in the nature of food seeking behavior and has been developed to produce a solution at continuous space. BitABC is a bitwise operator based binary ABC algorithm that can produce fast results in binary space. In this study, BitABC was improved to increase the local search capacity and adapted to the feature selection problem to measure the success of the proposed method. The results obtained using 10 data sets from UCI Machine Learning Repository indicate the success of the proposed method.

KW - Artificial Bee Colony

KW - Classification

KW - Feature selection

KW - Optimization

UR - https://www.scopus.com/pages/publications/85040635856

U2 - 10.1109/UBMK.2017.8093589

DO - 10.1109/UBMK.2017.8093589

M3 - Konferans katkısı

AN - SCOPUS:85040635856

T3 - 2nd International Conference on Computer Science and Engineering, UBMK 2017

SP - 165

EP - 170

BT - 2nd International Conference on Computer Science and Engineering, UBMK 2017

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 5 October 2017 through 8 October 2017

ER -

Özger ZB, Bolat B, Diri B. IBitABC: Lokal Arama ile Genişletilmiş İkili Yapay Ar Kolonisi Algoritmasi. In 2nd International Conference on Computer Science and Engineering, UBMK 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 165-170. 8093589. (2nd International Conference on Computer Science and Engineering, UBMK 2017). doi: 10.1109/UBMK.2017.8093589

IBitABC: Lokal Arama ile Genişletilmiş İkili Yapay Ar Kolonisi Algoritmasi

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap