Application of PCA-RBF Method to QSRR Studies on Hydrocarbon in FCC Gasoline with PCA-RBF

Abstract:

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A novel Artificial Neutral Network (ANN) algorithm based on Principle component analysis(PCA) is proposed and applied to predicted the retention index of a series of hydrocarbons in FCC gasoline. The PCA technology is utilized to preprocess the mass spectrogram of FCC gasoline for parameter selection and to reduce the input of prediction model, which thus improve the input factors and eliminates the correlation among the inputs. Then new sample data are input into radial basis function-artificial neutral network(RBF-ANN) to construct the prediction model.156 compounds were divided into two subsets. RSM of training set and testing set is 0.9958 and 0.9991, respectively. The satisfactory results were obtained.

Info:

Periodical:

Advanced Materials Research (Volumes 347-353)

Edited by:

Weiguo Pan, Jianxing Ren and Yongguang Li

Pages:

1769-1773

DOI:

10.4028/www.scientific.net/AMR.347-353.1769

Citation:

X. T. Zhang et al., "Application of PCA-RBF Method to QSRR Studies on Hydrocarbon in FCC Gasoline with PCA-RBF", Advanced Materials Research, Vols. 347-353, pp. 1769-1773, 2012

Online since:

October 2011

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Price:

$35.00

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