Evidence map›Paper›PMID 40615673›Full record

ArticleScientific reports2025

Hybrid Big Bang-Big crunch with cuckoo search for feature selection in credit card fraud detection.

Mohd Shukri Ab Yajid, Nilesh Bhosle, Gadug Sudhamsu, Ali Khatibi, Sahil Sharma, Rubal Jeet, R Sivaranjani, A Bhowmik, A Johnson Santhosh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mohd Shukri Ab YajidManagement and Science University, Shah Alam, Malaysia.
Nilesh BhosleDepartment of Computing Science and Artificial Intelligence, NIMS Institute of Engineering & Technology, NIMS University Rajasthan, Jaipur, India.
Gadug SudhamsuDepartment of Computer Science and Engineering, School of Engineering and Technology, JAIN (Deemed to be University), Bangalore, Karnataka, India.
Ali KhatibiManagement and Science University, Shah Alam, Malaysia.
Sahil SharmaDepartment of Computer Science and Engineering, Vivekananda Global University, 303012, Jaipur, Rajasthan, India.
Rubal JeetDepartment of Computer Science Engineering, Chandigarh Engineering College, Chandigarh Group of Colleges-Jhanjeri, 140307, Mohali, Punjab, India.
R SivaranjaniDepartment of Computer Science and Engineering, Raghu Engineering College, 531162, Visakhapatnam, Andhra Pradesh, India.
A BhowmikAssistant Professor, Department of Additive Manufacturing, Mechanical Engineering, SIMATS, Saveetha Institute of Medical and Technical Sciences, Thandalam, 602105, Chennai, India.
A Johnson SanthoshFaculty of Mechanical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia. johnson.antony@ju.edu.et.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The technological advancements of financial applications and the expansion of e-commerce platforms have increased the daily volume of credit card transactions. Consequently, there has been a substantial rise in instances of credit card fraud that leads to monetary losses for both individuals and financial institutions. The fraudsters continuously develop new technologies to breach security and acquire the credit card credentials of users through fraudulent activities such as scamming, phishing, or exploiting data breaches. There are numerous machine learning and deep learning techniques for detecting credit card frauds. However, due to the higher dimensionality and the imbalance between fraud and legitimate transactions, it becomes challenging to determine credit frauds with effective performance. To address the aforementioned issues, the current work has presented a novel hybrid Big Bang-Big crunch with cuckoo search (HB

Indexed as

Big Bang-Big crunchCredit card fraudsCuckoo searchDeep neural networksMetaheuristic

Identifiers

PMID40615673
PMCPMC12227623

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.