Certain Distance-Based Topological Indices of Parikh Word Representable Graphs

Thomas, Nobin; Mathew, Lisa; Sriram, S.; Nagar, Atulya K.; Subramanian, K. G.

doi:10.1155/2021/5567663

Cited by 5 publications

(3 citation statements)

References 36 publications

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“…The index in Equation 7 is also known as the Harary index (20). In endeavoring to relate graphic structures with the chemical structure, Parikh word representable graphs (PWRGs) were developed (21). These graphs were based on the Wiener or Harary index calculations.…”

Section: Molecular Descriptor Using Distance Indexesmentioning

confidence: 99%

Supervised Machine Learning-Graph Theory Approach For Analyzing the Electronic Properties of Alkanes

MOHAMED ZABİDİ,

ZAKARİA,

NAZİB ALİAS

2024

Journal of the Turkish Chemical Society Section A: Chemistry

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The combination of advanced scientific computing and quantum chemistry improves the existing approach in all chemistry and material science fields. Machine learning has revolutionized numerous disciplines within chemistry and material science. In this study, we present a supervised learning model for predicting the HOMO and LUMO energies of alkanes, which is trained on a database of molecular topological indices. We introduce a new moment topology approach has been introduced as molecular descriptors. Supervised learning utilizes artificial neural networks and support vector machines, taking advantage of the correlation between the molecular descriptors. The result demonstrate that this supervised learning model outperforms other models in predicting the HOMO and LUMO energies of alkanes. Additionally, we emphasize the importance of selecting appropriate descriptors and learning systems, as they play crucial role in accurately modeling molecules with topological orbitals.

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Section: Molecular Descriptor Using Distance Indexesmentioning

confidence: 99%

Supervised Machine Learning-Graph Theory Approach For Analyzing the Electronic Properties of Alkanes

MOHAMED ZABİDİ,

ZAKARİA,

NAZİB ALİAS

2024

Journal of the Turkish Chemical Society Section A: Chemistry

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“…is index got the attention of both applied and pure researchers. Some recent work on this index can be found in [21].…”

Section: Definitionmentioning

confidence: 99%

Topological Indices of Families of Bistar and Corona Product of Graphs

Khalid¹,

Kausar

Munir³

et al. 2022

Journal of Mathematics

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Topological indices are graph invariants that are used to correlate the physicochemical properties of a chemical compound with its (molecular) graph. In this study, we study certain degree-based topological indices such as Randić index, Zagreb indices, multiplicative Zagreb indices, Narumi–Katayama index, atom-bond connectivity index, augmented Zagreb index, geometric-arithmetic index, harmonic index, and sum-connectivity index for the bistar graphs and the corona product K m o K n ′ , where K n ′ represents the complement of complete graph K n .

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“…To study the paraffin boiling point, Harry Wiener [24] developed the first distance-based topological index. There are numerous different forms of topological indices, such as, vertex-degree based indices [25][26][27][28][29][30][31][32][33][34][35], distance-based indices [15,[36][37][38][39], and connection based indices [20,[40][41][42][43]. Among the numerous types of molecular descriptors, vertex-degree based molecular descriptors are commonly used [25-30, 44, 45], however, the connection based topological indices attracted significant attention of the researchers more recently due to their high predictive ability [20,43,46].…”

Section: Introductionmentioning

confidence: 99%

Connection based novel AL topological descriptors and structural property of the zinc oxide metal organic frameworks

Ullah,

Jamal,

Zaman

et al. 2024

Phys. Scr.

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Metal organic frameworks (MOFs) play a vital role in a variety of processes such as heterogeneous catalysis, heterogeneous gas purification and division, biocompatibility, toxicity, and biomedical applications. The Zinc-based MOFs, particularly, have gained prominence in the biomedical industry for applications such as drug delivery, biosensing, and cancer imaging, which has attracted the interest of researchers from around the world. Given the significant influence of molecular structure on the properties of MOFs, it is imperative to model and characterize this structure comprehensively to deepen our understanding and explore avenues for property enhancement. Topological indices are numerical parameters derived from the graph representation of molecules that quantify specific structural features. These indices provide insights into the connectivity and arrangement of atoms or nodes within the structure, offering information about its chemical, physical, or biological properties. In this study, the Zinc Oxide network structures are topologically modeled via connection numbers, and some novel topological descriptors viz. 〖AL〗_1, 〖AL〗_2, 〖AL〗_3, 〖AL〗_4, 〖AL〗_5, 〖AL〗_6, 〖AL〗_7 and〖 AL〗_8 are computed by deriving mathematical closed form expressions for them. Based on the numerical results, a comparative analysis of the computed topological descriptors is also performed. The prediction potential and chemical applicability of these indices are investigated using the benchmark dataset of Octane Isomers and corresponding experimental values, correlating experimental and computed values through regression models.

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Certain Distance-Based Topological Indices of Parikh Word Representable Graphs

Cited by 5 publications

References 36 publications

Supervised Machine Learning-Graph Theory Approach For Analyzing the Electronic Properties of Alkanes

Supervised Machine Learning-Graph Theory Approach For Analyzing the Electronic Properties of Alkanes

Topological Indices of Families of Bistar and Corona Product of Graphs

Connection based novel AL topological descriptors and structural property of the zinc oxide metal organic frameworks

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