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Lu J, Zhu L, Gao W. Cyclic connectivity index of bipolar fuzzy incidence graph. OPEN CHEM 2022. [DOI: 10.1515/chem-2022-0149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
In the performance characterization of chemical molecular structures, several uncertain properties are often encountered, and fuzzy theory is precisely the tool to characterize these uncertainties. When molecular structures are described by molecular graphs, the corresponding fuzzy graph theory is used to characterize the uncertainty of atoms and atomic bonds. In this study, there is introduced cyclic connectivity index and its average version for bipolar fuzzy incidence graph (BFIG), and several theoretical results are obtained in the light of graph theory and fuzzy theory. Finally, the given new fuzzy index is applied to the testing of anti-aging-related drugs yields average uncertainty data for the corresponding molecular structures.
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Affiliation(s)
- Juanjuan Lu
- School of Chemical and Environmental Engineering, Jiangsu University of Technology , Changzhou 213001 , China
| | - Linli Zhu
- School of Computer Engineering, Jiangsu University of Technology , Changzhou 213001 , China
| | - Wei Gao
- School of Information Science and Technology, Yunnan Normal University , Kunming 650500 , China
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