Applying migrating birds optimization to credit card fraud detection

Name: Applying migrating birds optimization to credit card fraud detection
Author: Elikucuk, I., Duman, Ekrem

İsim	Applying migrating birds optimization to credit card fraud detection
Yazar	Elikucuk, I., Duman, Ekrem
Basım Tarihi:	2013
Basım Yeri	- Springer Science+Business Media
Konu	Migrating birds optimization algorithm, Fraud, Credit cards, Genetic algorithms
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-3-642-40319-4
Kayıt Numarası	1681cf4a-6f02-4f31-920a-529e67056333
Lokasyon	Industrial Engineering
Tarih	2013
Örnek Metin	We discuss how the Migrating Birds Optimization algorithm (MBO) is applied to statistical credit card fraud detection problem. MBO is a recently proposed metaheuristic algorithm which is inspired by the V flight formation of the migrating birds and it was shown to perform very well in solving a combinatorial optimization problem, namely the quadratic assignment problem. As analyzed in this study, it has a very good performance in the fraud detection problem also when compared to classical data mining and genetic algorithms. Its performance is further increased by the help of some modified neighborhood definitions and benefit mechanisms.
DOI	10.1007/978-3-642-40319-4_36
Cilt	7867

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Applying migrating birds optimization to credit card fraud detection

Yazar Elikucuk, I., Duman, Ekrem

Basım Tarihi 2013

Basım Yeri - Springer Science+Business Media

Konu Migrating birds optimization algorithm, Fraud, Credit cards, Genetic algorithms

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-3-642-40319-4

Kayıt Numarası 1681cf4a-6f02-4f31-920a-529e67056333

Lokasyon Industrial Engineering

Tarih 2013

Örnek Metin We discuss how the Migrating Birds Optimization algorithm (MBO) is applied to statistical credit card fraud detection problem. MBO is a recently proposed metaheuristic algorithm which is inspired by the V flight formation of the migrating birds and it was shown to perform very well in solving a combinatorial optimization problem, namely the quadratic assignment problem. As analyzed in this study, it has a very good performance in the fraud detection problem also when compared to classical data mining and genetic algorithms. Its performance is further increased by the help of some modified neighborhood definitions and benefit mechanisms.

DOI 10.1007/978-3-642-40319-4_36

Cilt 7867