A Simplified Algorithm for Identifying Abnormal Changes in Dynamic Networks
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Publication:6414158
DOI10.1016/J.PHYSA.2022.128224arXiv2210.08891MaRDI QIDQ6414158
Bertrand Michel, Bouchaib Azamir, Driss Bennis
Publication date: 17 October 2022
Abstract: Topological data analysis has recently been applied to the study of dynamic networks. In this context, an algorithm was introduced and helps, among other things, to detect early warning signals of abnormal changes in the dynamic network under study. However, the complexity of this algorithm increases significantly once the database studied grows. In this paper, we propose a simplification of the algorithm without affecting its performance. We give various applications and simulations of the new algorithm on some weighted networks. The obtained results show clearly the efficiency of the introduced approach. Moreover, in some cases, the proposed algorithm makes it possible to highlight local information and sometimes early warning signals of local abnormal changes.
Economic time series analysis (91B84) Other homology theories in algebraic topology (55N35) Applied homological algebra and category theory in algebraic topology (55U99) Statistical mechanics, structure of matter (82-XX)
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