Clustering method based on the elastic energy functional of directed signed weighted graphs

Alexander Tselykh, Vladislav Vasilev and Larisa Tselykh

Physica A: Statistical Mechanics and its Applications, 2019, vol. 523, issue C, 392-407

Abstract: This article proposes a new method of clustering based on minimizing the elastic energy functional (EEF) of directed weighted signed graphs. The new method has three distinctive features: the weights on the edges of the graph are set by the original model of the system (fuzzy cognitive map), and each weight represents a causal relationship between the graph vertices (system factors); a clearly formalized criterion for division into clusters; and the order of the vertices generated by the algorithm reflects the ratio of intra-cluster and extra-cluster energy. The proposed functional of the elastic energy reflects the nature of the factor relationship in a socio-economic system. Minimization of the functional is monotonic and does not require user intervention. The algorithm is computationally efficient.

Keywords: Elastic energy functional; Directed weighted graphs; Clustering detection; Optimization methods (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:523:y:2019:i:c:p:392-407

DOI: 10.1016/j.physa.2019.02.031

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