Prediction of air-to-blood partition coefficients of volatile organic compounds using genetic algorithm and artificial neural network

Analytica Chimica Acta

Volumn 619, Issue 2, 2008, Pages 157-164

  Konoz, Elahe ^a   Golmohammadi, Hassan ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b UNIVERSITY OF MAZANDARAN   (Iran)

Author keywords

Air to blood partition coefficient; Artificial neural network; Genetic algorithm; Multiple linear regression

Indexed keywords

CARRIER CONCENTRATION; DATA STRUCTURES; GENETIC ALGORITHMS; LINEAR REGRESSION; NEURAL NETWORKS; NONLINEAR ANALYSIS;

AIR-TO-BLOOD PARTITION COEFFICIENT; MULTIPLE LINEAR REGRESSION (MLR); NEGATIVE ATOM; PARTIAL CHARGE;

VOLATILE ORGANIC COMPOUNDS;

VOLATILE ORGANIC COMPOUND;

ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; ATOM; CORRELATION ANALYSIS; ELECTRON; GENETIC ALGORITHM; MULTIPLE LINEAR REGRESSION ANALYSIS; PARTITION COEFFICIENT; PREDICTION; PRIORITY JOURNAL; VALIDATION STUDY;

AIR; ALGORITHMS; MODELS, GENETIC; NEURAL NETWORKS (COMPUTER); ORGANIC CHEMICALS; VOLATILIZATION;

EID: 46549083156     PISSN: 00032670     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aca.2008.04.065     Document Type: Article

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