Metaheuristic and Data Mining Algorithms-based Feature Selection Approach for Anomaly Detection-Reference-Cited by-同舟云学术

Metaheuristic and Data Mining Algorithms-based Feature Selection Approach for Anomaly Detection

Published:2024-01-15 Issue: Volume: Page:1-15
ISSN:0377-2063
Container-title:IETE Journal of Research
language:en
Short-container-title:IETE Journal of Research

Author:

Nemati Zahra¹,Mohammadi Ali¹,Bayat Ali¹,Mirzaei Abbas²

Affiliation:

1. Department of Accounting, Zanjan Branch, Islamic Azad University, Zanjan, Iran

2. Department of Computer Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/03772063.2023.2299673

Reference33 articles.

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3. Unsupervised real-time anomaly detection for streaming data

4. Use of Logistic Regression in Identification of Anomaly Financial Reporting;Etemadi H.;Audit Knowledge,2013

5. Committee of Audit Standards, Standards and Principles of Accounting and Auditing: Audit Standards. Tehran, Iran: Audit Organisation Publications, 2015.

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