Title: Research on automatic recognition of electronic communication information anomalies based on fuzzy association rules

Authors: Ying He

Addresses: School of Electronic Information Engineering, Xi'an Siyuan University, Xi'an, 710038, China

Abstract: In order to improve the accuracy and efficiency of electronic communication information anomaly recognition, this paper proposes the research of electronic communication information anomaly automatic recognition based on fuzzy association rules. Firstly, obtain electronic communication information, and perform attribute extraction, missing value filling, data de-duplication, and data synchronisation. Secondly, the membership matrix of the sample set is constructed, and the fuzzy grade of communication information is determined by fuzzy association rules to achieve the classification of electronic communication information anomaly types; then, K-means++ algorithm is used to optimise the selection of initial centroid. Finally, K-FKNN is used to complete the automatic identification of electronic communication information anomalies. The experimental results show that the anomaly information capture rate of this method is 100%, the recognition accuracy is 98%, and the recognition time is only 16 s.

Keywords: Lagrange multiplier method; fuzzy association rules; membership matrix; fuzzy grade; K-means++ algorithm.

DOI: 10.1504/IJRIS.2024.142354

International Journal of Reasoning-based Intelligent Systems, 2024 Vol.16 No.4, pp.298 - 306

Received: 03 Feb 2023
Accepted: 21 Mar 2023
Published online: 25 Oct 2024 *

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