A novel method for analyzing inverse problem of topological indices of graphs using competitive agglomeration

Rongling Lang, Tao Li, Desen Mo and Yongtang Shi

Applied Mathematics and Computation, 2016, vol. 291, issue C, 115-121

Abstract: A novel method for analyzing the inverse problem of topological indices of graph is proposed in this paper, which applies the data mining technique to classification of graphs according to topological indices. Differing from the way of using topological indices to categorize graphs into different isomorphic classes, this method aims at dividing molecular graphs with n vertices into several compact classes according to their topological indices. Then the chemical and physical features of each kind of graph can be researched and new compounds can be found, which has great significance on bio-medical filed. In the experiment, three classes of simple connected graphs with 5, 6 and 7 vertices, respectively, are investigated and analyzed using the proposed method, the experimental results show the validity of it. However, there are still some problems needed to be researched further, such as selecting the vector of topological indices for clustering, selecting the distance between the vectors of topological indices, choosing the aspects to analyze the properties of each kind of graph after clustering, etc.

Keywords: Graph theory; Topological index; Competitive agglomeration; Data mining (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:291:y:2016:i:c:p:115-121

DOI: 10.1016/j.amc.2016.06.048

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