QSBR study of substituted phenols and benzoic acids

Article type: Research Article

Authors: Lu, Guang-hua | Wang, Chao | Yuan, Xing | Zhao, Yuan-hui

Affiliations: College of Water Resources and Environment, Hohai University, Nanjing 210098, China | Department of Environmental Science, Northeast Normal University, Changchun 130024, China

Abstract: The biodegradability of 30 substituted phenols and benzoic acids was determined by BOD technique. The molecular weight (MW), heat of formation (Hf) and the energy of the highest occupied molecular orbital (EHOMO) of the studied compounds were calculated by the quantum chemical method MOPAC6.0-AM1. The quantitative structure-biodegradability relationships (QSBRs) were developed by the linear regression method and neural network approach, respectively. It has been shown that the neural network method is able to provide a superior fit to the training set data and test set data and produce a lower prediction error than the linear regression method.

Keywords: BOD, regression, artificial neural network, prediction

Journal: Journal of Environmental Sciences, vol. 15, no. 1, pp. 88-91, 2003