A novel clustering method based on quasi-consensus motions of dynamical multiagent systems
type: Item
instance of: scholarly article
title: A novel clustering method based on quasi-consensus motions of dynamical multiagent systems
zbMATH Open document ID: 1373.93010
DOI: 10.1155/2017/4978613
author: Ning Cai
author: Chen Diao
author: M. Junaid Khan
published in: Complexity
publication date: 2017-10-26T00:00:00Z
review text: Summary: This paper presents a novel approach for clustering, which is based on quasi-consensus of dynamical linear high-order multiagent systems. The graph topology is associated with a selected multiagent system, with each agent corresponding to one vertex. In order to reveal the cluster structure, the agents belonging to a similar cluster are expected to aggregate together. To establish the theoretical foundation, a necessary and sufficient condition is given to check the achievement of group consensus. Two numerical instances are furnished to illustrate the results of our approach.
Mathematics Subject Classification ID: 93A14
Mathematics Subject Classification ID: 68T42
Mathematics Subject Classification ID: 05C90
zbMATH DE Number: 6798459
zbMATH Keywords: clustering method
zbMATH Keywords: quasi-consensus motions
zbMATH Keywords: dynamical multiagent systems
zbMATH Keywords: graph topology
zbMATH Keywords: group consensus
describes a project that uses: clusfind
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/4978613
OpenAlex ID: W2755424168
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description: scientific article; zbMATH DE number 6798459