Cyclic connectivity index of bipolar fuzzy incidence graph

Lu, Juanjuan; Zhu, Linli; Gao, Wei

doi:10.1515/chem-2022-0149

Cited by 2 publications

(1 citation statement)

References 33 publications

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“…Chemical graph theory is a key branch of theoretical chemistry, whose main task is to estimate the performance of compounds by means of the calculation of topological parameter of molecular structures, where the atoms and chemical bonds of compounds are represented by vertices and edges respectively. The results obtained from chemical graph theory are consistent with experiments, which makes this method popular in chemistry, materials science, pharmacy and other related fields (Gao et al [7] and Lu et al [8]).…”

Section: Introductionsupporting

confidence: 79%

Remarks on bipolar cubic fuzzy graphs and its chemical applications

Zhu

Gao

2023

International Journal of Mathematics and Computer in Engineering

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In theoretical chemistry, fuzzy molecular graphs can be used to model chemical molecular structures with uncertainty information, where the vertex membership function and edge membership function describe the uncertainty of atoms and chemical bonds respectively. This paper studies chemical topological index of bipolar cubic fuzzy graphs. The new concepts and theorems are given in terms of graph theory and fuzzy set theory approaches and several theoretical conclusions on bipolar Wiener index of bipolar cubic fuzzy graphs are determined. Furthermore, we apply it in chemical science and calculate the bipolar Wiener index of dimethyltryptamine and hallucinogen which are modelled by bipolar cubic fuzzy graphs.

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Section: Introductionsupporting

confidence: 79%

Remarks on bipolar cubic fuzzy graphs and its chemical applications

Zhu

Gao

2023

International Journal of Mathematics and Computer in Engineering

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The connectivity indices concept of neutrosophic graph and their application of computer network, highway system and transport network flow

Kaviyarasu,

Aslam,

Afzal

et al. 2024

Sci Rep

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To address information ambiguities, this study suggests using neutrosophic sets as a tactical tool. Three membership functions (called $$T_r, I_n, $$ T r , I n , and $$ F_i$$ F i ) that indicate an object’s degree of truth, indeterminacy, and false membership constitute the neutrosophic set. It becomes clear that the neutrosophic connectivity index (CIN) is an essential tool for solving practical problems, especially those involving traffic network flow. To capture uncertainties, neutrosophic graphs are used to represent knowledge at different membership levels. Two types of $$CIN_s,$$ C I N s , mean CIN and CIN, are investigated within the framework of neutrosophic graphs. In the context of neutrosophic diagrams, certain node types-such as neutrosophic neutral nodes, neutrosophic connectivity reducing nodes (NCRN) , and neutrosophic graph connectivity enhancing nodes (NCEN) , play important roles. We concentrate on two types of networks, specifically traffic network flow, to illustrate the real-world uses of CIN. By comparing results, one can see how junction removal affects network connectivity using metrics like Connectivity Indexes (CIN) and Average Connectivity Indexes (ACIN) . A few nodes in particular, designated by ACIN as Non-Critical Removal Nodes $$ (NCRN_s) $$ ( N C R N s ) , show promise for increases in average connectivity following removal. To fully comprehend traffic network dynamics and make the best decisions, it is crucial to take into account both ACIN and CIN insights. This is because different junctions have different effects on average and overall connectivity metrics.

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Cyclic connectivity index of bipolar fuzzy incidence graph

Cited by 2 publications

References 33 publications

Remarks on bipolar cubic fuzzy graphs and its chemical applications

Remarks on bipolar cubic fuzzy graphs and its chemical applications

The connectivity indices concept of neutrosophic graph and their application of computer network, highway system and transport network flow

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