کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4980903 | 1367843 | 2016 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
QSPR estimation of the auto-ignition temperature for pure hydrocarbons
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بهداشت و امنیت شیمی
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چکیده انگلیسی
Due to the combustible nature of hydrocarbons, accurate safety information for their safe utilization and transport is essential. The autoignition temperature (AIT) is an important safety parameter. In this study, a quantitative structure-property relationship (QSPR) approach was utilized to present a predictive model for the estimation of the AIT of 813 hydrocarbons from 69 different chemical families. A unified three-parameter model was constructed combining multivariate linear regression (MLR) and a genetic algorithm (GA). In order to investigate the complex performance of the selected molecular parameters an optimized artificial neural network (ANN) model was developed. The resulting models showed good prediction ability. Although the ANN prediction results are more accurate than the GA-MLR model, the application of the latter is more convenient.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Process Safety and Environmental Protection - Volume 103, Part A, September 2016, Pages 115-125
Journal: Process Safety and Environmental Protection - Volume 103, Part A, September 2016, Pages 115-125
نویسندگان
Tohid Nejad Ghaffar Borhani, Afsaneh Afzali, Mehdi Bagheri,