首页|A Self-Adapting and Efficient Dandelion Algorithm and Its Application to Feature Selection for Credit Card Fraud Detection

A Self-Adapting and Efficient Dandelion Algorithm and Its Application to Feature Selection for Credit Card Fraud Detection

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A dandelion algorithm(DA)is a recently developed intelligent optimization algorithm for function optimization prob-lems.Many of its parameters need to be set by experience in DA,which might not be appropriate for all optimization problems.A self-adapting and efficient dandelion algorithm is proposed in this work to lower the number of DA's parameters and simplify DA's structure.Only the normal sowing operator is retained;while the other operators are discarded.An adaptive seeding radius strat-egy is designed for the core dandelion.The results show that the proposed algorithm achieves better performance on the standard test functions with less time consumption than its competitive peers.In addition,the proposed algorithm is applied to feature selection for credit card fraud detection(CCFD),and the results indicate that it can obtain higher classification and detection per-formance than the-state-of-the-art methods.

Credit card fraud detection(CCFD)dandelion algorithm(DA)feature selectionnormal sowing operator

Honghao Zhu、MengChu Zhou、Yu Xie、Aiiad Albeshri

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School of Computer and Information Engineering,Bengbu University,Bengbu 233030,China

School of Information and Electronic Engineering,Zhejiang Gongshang University,Hangzhou 310018,China,Helen and John C.Hartmann,the Department of Electrical and Computer Engineering,New Jersey Institute of Technology,Newark NJ 07102 USA

College of Information Engineering,Shanghai Maritime University,Shanghai 201306,China

Department of Computer Science,King Abdulaziz University,Jeddah 21481,Saudi Arabia

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Institutional Fund ProjectsKey Projects of Natural Science Research in Anhui Higher Education InstitutionsProvincial Quality Project of Colleges and Universities in Anhui ProvinceProvincial Quality Project of Colleges and Universities in Anhui ProvinceBengbu University 2021 High-Level Scientific Research and Cultivation Project

IFPIP-1481-611-14432022 AH0519092022sdxx0202022xqhz0442021pyxm04

2024

10.1109/JAS.2023.124008

自动化学报(英文版)
中国自动化学会,中国科学院自动化研究所,中国科技出版传媒股份有限公司

自动化学报(英文版)

CSTPCDEI
ISSN：2329-9266
年,卷(期)：2024.11(2)
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