Prediction of atmospheric degradation data for POPs by gene expression programming.
Quantitative structure-activity relationship models for the prediction of the mean and the maximum atmospheric degradation half-life values of persistent organic pollutants were developed based on the linear heuristic method (HM) and non-linear gene expression programming (GEP). Molecular descriptors, calculated from the structures alone, were used to represent the characteristics of the compounds. HM was used both to pre-select the whole descriptor sets and to build the linear model. GEP yielded satisfactory prediction results: the square of the correlation coefficient r(2) was 0.80 and 0.81 for the mean and maximum half-life values of the test set, and the root mean square errors were 0.448 and 0.426, respectively. The results of this work indicate that the GEP is a very promising tool for non-linear approximations.
Department of Applied Chemistry, Yantai University, Yantai, Shandong, P.R. China. fluan@sina.com
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Luan
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Si
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Liu
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Wen
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Zhang
D001185:Artificial Intelligence; D001274:Atmospheric Pressure; D004785:Environmental Pollutants / Q000737:chemistry / Q000378:metabolism* / Q000633:toxicity; D005786:Gene Expression Regulation / Q000502:physiology*; D015386:Hazardous Substances; D016014:Linear Models; D009930:Organic Chemicals / Q000737:chemistry / Q000378:metabolism* / Q000633:toxicity; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship
D004785:Environmental Pollutants; D015386:Hazardous Substances; D009930:Organic Chemicals