An accurate model for prediction of autoignition temperature of pure compounds

Journal of Hazardous Materials

Volumn 189, Issue 1-2, 2011, Pages 211-221

  Gharagheizi, Farhad ^a  

^a Saman Energy Giti Co   (Iran)

Author keywords

Artificial Neural Networks; Autoignition temperature (AIT); Combustion; Group contribution

Indexed keywords

ACCURATE PREDICTION; ARTIFICIAL NEURAL NETWORK; AUTOIGNITION TEMPERATURE; AUTOIGNITION TEMPERATURE (AIT); CHEMICAL FAMILY; EXPERIMENTAL VALUES; GROUP CONTRIBUTION; GROUP CONTRIBUTIONS; PREDICTIVE MODELS; PURE COMPOUNDS; ROOT MEAN SQUARE ERRORS; SQUARED CORRELATION COEFFICIENTS;

CHEMICAL COMPOUNDS; COMBUSTION;

NEURAL NETWORKS;

CHEMICAL COMPOUND;

ARTIFICIAL NEURAL NETWORK; COMBUSTION; CORRELATION; ERROR ANALYSIS; NUMERICAL MODEL; TEMPERATURE PROFILE;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOIGNITION TEMPERATURE; MATHEMATICAL MODEL; PREDICTION; TEMPERATURE MEASUREMENT;

CHEMICAL PROCESSES; FIRES; MODELS, CHEMICAL; NEURAL NETWORKS (COMPUTER); QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; TEMPERATURE;

EID: 79953780796     PISSN: 03043894     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhazmat.2011.02.014     Document Type: Article

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