ArticleScientific reports2025
Hybrid arithmetic optimization algorithm for telecom network anomaly detection.
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.
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Abstract
This study introduces the Opposition Based learning (OB) algorithm and Nelder-Mead (NM) algorithm coupled with the Arithmetic Optimization Algorithm (AOA) via hybridization mechanism called OBAOANM to enhance the detection accuracy of telecom network anomalies. The proposed algorithm OBAOANM features extending the exploitation and exploration phases of AOA algorithm into OB and NM algorithms to improve identification of network bypass anomalies The broad-spectrum benefit of the proposed algorithm is to boost the identification precision of telecom network intrusion detection (NID) capabilities thus making the OBAOANM algorithm a more suitable tool for solving network traffic problems. The experimental results prove that this OBAOANM algorithm aids maximizing classification accuracies of NID by attaining an average of 93.10% of the overall comparative experimentations.
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