Regression analysis of benzenoid hydrocarbons using distance-based topological indices, which are effective predictors of physical properties of benzenoid hydrocarbons, including benzene, naphthalene, phenanthrene, anthracene, and pyrene
	GOVINDAN V; PIRIADARSHANI D; NAYAKI P M
	2025-04-04
专利权人	GOVINDAN V (GOVI-Individual) ; PIRIADARSHANI D (PIRI-Individual) ; NAYAKI P M (NAYA-Individual) ; HINDUSTAN INST TECHNOLOGY & SCI (HIND-Non-standard)
申请日期	2025-04-04
专利号	IN202541033495-A
成果简介	NOVELTY - Regression analysis of benzenoid hydrocarbons using distance-based topological indices, where Mostar and Szeged distance-based topological indices are effective predictors of the physical properties of benzenoid hydrocarbons, including benzene, naphthalene, phenanthrene, anthracene, and pyrene. USE - Regression analysis of benzenoid hydrocarbons using distance-based topological indices. ADVANTAGE - The Mostar and Szeged indices can serve as valuable tools for modeling and predicting the physical characteristics of benzenoid hydrocarbons within the domain of chemical informatics. The insights gained from the study lay the groundwork for further exploration of the predictive capabilities of topological indices for other classes of organic compounds, enhancing their applicability in molecular modeling and related fields. The methodology leverages topological indices to facilitate property prediction, thus reducing the dependence on experimental techniques and streamlining molecular design processes. The study provides superior predictive accuracy for the selected physical properties, which can be determined through robust statistical evaluation. A significant correlation has been identified between the calculated Mostar and Szeged indices and key physical properties, such as standard enthalpy of formation and boiling points, thus demonstrating a quantitative link between molecular structure and physical behavior.
IPC 分类号	C07C-051/31 ; G01N-025/48 ; G01N-029/44 ; G06F-017/18 ; G06N-020/00
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/13207
专题	中国科学院新疆生态与地理研究所
作者单位	1.GOVINDAN V (GOVI-Individual) 2.PIRIADARSHANI D (PIRI-Individual) 3.NAYAKI P M (NAYA-Individual) 4.HINDUSTAN INST TECHNOLOGY & SCI (HIND-Non-standard)
推荐引用方式 GB/T 7714	GOVINDAN V,PIRIADARSHANI D,NAYAKI P M. Regression analysis of benzenoid hydrocarbons using distance-based topological indices, which are effective predictors of physical properties of benzenoid hydrocarbons, including benzene, naphthalene, phenanthrene, anthracene, and pyrene. IN202541033495-A[P]. 2025.

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