Abstract
Graph theory is a fundamental and energetic tool for designing and modeling a graph/network. There are certain topological indices based on degree, distance and eccentricity, etc. The topological indices essentially relate certain physio-concoction properties and bio-Activity to the corresponding synthetic and atomic structure. In this paper, our aim is to figure out degree-based topological indices mainly atom-bond connectivity (ABC), geometric-Arithmetic (GA), ABC4 and GA5 indices for cellular neural network (CNN) and give closed results of these indices for cellular neural network. Moreover, we also compute general Randi cindex R of CNN for = { 1 ,-1 , 1 2 ,-1 2 } only and give analytical closed form results. A 3D graph analysis for comparison of indices is also given.
Original language | English |
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Pages (from-to) | 3605-3614 |
Number of pages | 10 |
Journal | Journal of Intelligent and Fuzzy Systems |
Volume | 37 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2019 |
Keywords
- Molecular descriptor
- atom bond connectivity index
- cellular neural network
- general Randić index
- geometric arithmetic index
ASJC Scopus subject areas
- Statistics and Probability
- General Engineering
- Artificial Intelligence