title: Prediction of the competitive adsorption isotherms of 2-phenylethanol and 3-phenylpropanol by artificial neural networks.
abstract: Artificial neural networks (ANNs) were regarded as data-mapping networks with strong nonlinear fitting abilities. A 2-6-2 network was used to determine the competitive adsorption isotherm of 2-phenylethanol (PE) and 3-phenylpropanol (PP). The ANN results were forms of data mapping rather than theoretical mathematical model. The ANN architecture was established after training with a set of experimental data. The established ANN was applied to predict the adsorption isotherms of PE and PP. The selection of parameters for the ANN was discussed. The results indicate that ANN has excellent potential for use in non-linear chromatography for the prediction of adsorption isotherms.
authors: Department of Chemical and Engineering, University of Science and Technology of Liaoning, Anshan, Liaoning 114051, China. Electronic address: wxh93@163.com.
authors: Xiuhong
authors: X
authors: Wu
authors: Department of Chemical and Engineering, University of Science and Technology of Liaoning, Anshan, Liaoning 114051, China.
authors: Shaoyan
authors: S
authors: Wang
authors: Department of Chemical and Engineering, University of Science and Technology of Liaoning, Anshan, Liaoning 114051, China.
authors: Renzhuang
authors: R
authors: Zhang
authors: School of Material Science and Engineering, Tianjin University, Tianjin 300072, China.
authors: Zhiming
authors: Z
authors: Gao
mesh_terms: D000327:Adsorption; D002845:Chromatography; D008956:Models, Chemical; D016571:Neural Networks, Computer; D010626:Phenylethyl Alcohol / Q000737:chemistry*; D020005:Propanols / Q000737:chemistry*
chemical_list: D020005:Propanols; C016655:3-phenylpropanol-1; D010626:Phenylethyl Alcohol
keywords: Adsorption isotherm; Artificial neural network; Binary component; Fitting; Modeling