QSPR Study on Gross Heat of Combustion of Nitro Aromatic Compounds Based on Genetic Algorithm

Rui Wang; Hong Yin Cao; Quan Sheng Kang; Zhen Ming Li

doi:10.4028/www.scientific.net/AMR.750-752.2248

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 750-752QSPR Study on Gross Heat of Combustion of Nitro...

QSPR Study on Gross Heat of Combustion of Nitro Aromatic Compounds Based on Genetic Algorithm

Abstract:

A novel QSPR model was proposed as to predict the gross heat of combustion of 32 nitro aromatic compounds. Genetic algorithm (GA) was applied to select the optimal subset of the molecular structures descriptors most related to gross heat of combustion. The multiple linear regression (MLR) was taken to build a prediction model of gross heat of combustion for the 32 compounds. The correlation coefficients (R²) together with correlation coefficient of the leave-one-out cross validation (Q²_CV) of the model is 0.997 and 0.995, respectively. The new model is highly statistically significant, and the robustness as well as internal prediction capability of which is satisfactory. This study can provide a new way for predicting the gross heat of combustion of nitro aromatic compounds for engineering.

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Periodical:

Advanced Materials Research (Volumes 750-752)

Pages:

2248-2251

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.750-752.2248

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Online since:

August 2013

Authors:

Rui Wang, Hong Yin Cao, Quan Sheng Kang, Zhen Ming Li

Keywords:

Genetic Algorithm (GA), Gross Heat of Combustion, Nitro Aromatic Compounds, Quantitative Structure-Property Relationship (QSPR)

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