Predicting Impact Sensitivity of Heterocyclic Nitroarenes from Molecular Structures Selected by Genetic Algorithm

Rui Wang; Yong Gu Wang; Hui Liu

doi:10.4028/www.scientific.net/AMR.535-537.2550

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 535-537Predicting Impact Sensitivity of Heterocyclic...

Predicting Impact Sensitivity of Heterocyclic Nitroarenes from Molecular Structures Selected by Genetic Algorithm

Abstract:

A novel theoretical model was constructed to predict the impact sensitivity of 44 heterocyclic nitroarenes. The optimal subset of the molecular structures descriptors were selected by genetic algorithm (GA). The multiple linear regression (MLR) was then applied to build a prediction model of impact sensitivity for the 44 compounds. The correlation coefficients (R2) together with correlation coefficient of the leave-one-out cross validation (Q2CV) of the model is 0.928 and 0.865, respectively. The new model is highly statistically significant, and the robustness as well as internal prediction capability of which is satisfactory. The predicted impact sensitivity values are in good agreement with the experimental data.

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Periodical:

Advanced Materials Research (Volumes 535-537)

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2550-2553

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.535-537.2550

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Online since:

June 2012

Authors:

Rui Wang, Yong Gu Wang, Hui Liu

Keywords:

Genetic Algorithm (GA), Heterocyclic Nitroarenes, Impact Sensitivity, Molecular Structures

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