Modeling of acyclic carbonyl compounds normal boiling points by correlation weighting of nearest neighboring codes

A. A. Toropov; A. P. Toropova

doi:10.1016/S0166-1280(01)00733-3

Modeling of acyclic carbonyl compounds normal boiling points by correlation weighting of nearest neighboring codes

A. A. Toropov, A. P. Toropova

Istituto di Ricerche Farmacologiche "Mario Negri"

Research output: Contribution to journal › Article › peer-review

Abstract

The nearest neighboring code (NNC) is a local graph invariant. The NNC of a given vertex of the labeled hydrogen filled graph (LHFG) is a function of atom composition of the vertex neighbors. By optimization the correlation weights of different atoms and different values of the NNCs, one-variable models of the normal boiling points of carbonyl compounds have been obtained. Statistical characteristics of the best of such model are as follows: training set: n = 100, r² = 0.972, s = 6.12°C, F = 3464; test set: n = 100, r² = 0.975, s = 6.00°C, F = 3905.

Original language	English
Pages (from-to)	11-15
Number of pages	5
Journal	Journal of Molecular Structure: THEOCHEM
Volume	581
DOIs	https://doi.org/10.1016/S0166-1280(01)00733-3
Publication status	Published - Apr 5 2002

Keywords

Acyclic carbonyl compounds normal boiling points
Correlation weights
Optimal descriptors
QSPR

ASJC Scopus subject areas

Physical and Theoretical Chemistry
Computational Theory and Mathematics
Atomic and Molecular Physics, and Optics

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10.1016/S0166-1280(01)00733-3

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title = "Modeling of acyclic carbonyl compounds normal boiling points by correlation weighting of nearest neighboring codes",

abstract = "The nearest neighboring code (NNC) is a local graph invariant. The NNC of a given vertex of the labeled hydrogen filled graph (LHFG) is a function of atom composition of the vertex neighbors. By optimization the correlation weights of different atoms and different values of the NNCs, one-variable models of the normal boiling points of carbonyl compounds have been obtained. Statistical characteristics of the best of such model are as follows: training set: n = 100, r2 = 0.972, s = 6.12°C, F = 3464; test set: n = 100, r2 = 0.975, s = 6.00°C, F = 3905.",

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T1 - Modeling of acyclic carbonyl compounds normal boiling points by correlation weighting of nearest neighboring codes

AU - Toropov, A. A.

AU - Toropova, A. P.

PY - 2002/4/5

Y1 - 2002/4/5

N2 - The nearest neighboring code (NNC) is a local graph invariant. The NNC of a given vertex of the labeled hydrogen filled graph (LHFG) is a function of atom composition of the vertex neighbors. By optimization the correlation weights of different atoms and different values of the NNCs, one-variable models of the normal boiling points of carbonyl compounds have been obtained. Statistical characteristics of the best of such model are as follows: training set: n = 100, r2 = 0.972, s = 6.12°C, F = 3464; test set: n = 100, r2 = 0.975, s = 6.00°C, F = 3905.

AB - The nearest neighboring code (NNC) is a local graph invariant. The NNC of a given vertex of the labeled hydrogen filled graph (LHFG) is a function of atom composition of the vertex neighbors. By optimization the correlation weights of different atoms and different values of the NNCs, one-variable models of the normal boiling points of carbonyl compounds have been obtained. Statistical characteristics of the best of such model are as follows: training set: n = 100, r2 = 0.972, s = 6.12°C, F = 3464; test set: n = 100, r2 = 0.975, s = 6.00°C, F = 3905.

KW - Acyclic carbonyl compounds normal boiling points

KW - Correlation weights

KW - Optimal descriptors

KW - QSPR

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Modeling of acyclic carbonyl compounds normal boiling points by correlation weighting of nearest neighboring codes

Abstract

Keywords

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