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Issue title: Special Section: Applied Machine Learning and Management of Volatility, Uncertainty, Complexity & Ambiguity (V.U.C.A)
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Hu, Haiyana; * | Su, Changb
Affiliations: [a] Department of Engineering, Jilin Business and Technology College, Changchun, China | [b] Information Center, Changchun Eleventh High School, Changchun, China
Correspondence: [*] Corresponding author. Haiyan Hu, Department of Engineering, Jilin Business and Technology College, Changchun 130507, China. E-mail: haiyanhuu@21cn.com.
Abstract: In order to overcome the problems of invulnerability and low communication efficiency when analyzing network communication instability with current methods, this paper proposes a modeling method of network communication instability based on K-means algorithm. The network element nodes are generated by clustering idea, and the initial communication topology is constructed. K-means algorithm is used to optimize the initial communication model, build a comprehensive mathematical model of network communication, and solve the model to realize the optimization of communication model. The network efficiency function is used to further quantify the network invulnerability, and the function is used to find the most vulnerable nodes in the network, and strengthen them to achieve efficient control of network invulnerability. The experimental results show that the model has strong invulnerability, up to 99.9%, high communication efficiency and coverage, and the maximum communication delay is only 0.35 s. It is a feasible network communication model.
Keywords: K-means algorithm, network communication, Instability, modeling
DOI: 10.3233/JIFS-179938
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1649-1658, 2020
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