Affiliation:
1. College of Big Data Statistics, Guizhou University of Finance and Economics, Guiyang, Guizhou 550025, China
2. Department of Applied Mathematics, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, China
Abstract
Network similarity measures have proven essential in the field of network analysis. Also, topological indices have been used to quantify the topology of networks and have been well studied. In this paper, we employ a new topological index which we call the Ediz eccentric connectivity index. We use this quantity to define network similarity measures as well. First, we determine the extremal value of the Ediz eccentric connectivity index on some network classes. Second, we compare the network similarity measure based on the Ediz eccentric connectivity index with other well-known topological indices such as Wiener index, graph energy, Randić index, the largest eigenvalue, the largest Laplacian eigenvalue, and connectivity eccentric index. Numerical results underpin the usefulness of the chosen measures. They show that our new measure outperforms all others, except the one based on Wiener index. This means that the measure based on Wiener index is still the best, but the new one has certain advantage to some extent.
Funder
National Natural Science Foundation of China
Subject
Multidisciplinary,General Computer Science
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