Paper Title:
Application of BP Neural Network into the Kow of Chemical Contaminants
  Abstract

The octanol / water partition coefficient (Kow) is an important physical parameters to describe their behavior in the environment. However, because of some reasons, it is difficult to determine the octanol / water partition coefficient of each compound accurately. In this paper, we will introduce RBF neural network and molecular bond connectivity index to forecast the solubility of organic compounds in water. The result is better using the BP network to predict, the correlation coefficient has achieved 0.998, the prediction error in the permission scope.

  Info
Periodical
Advanced Materials Research (Volumes 121-122)
Edited by
Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo
Pages
574-578
DOI
10.4028/www.scientific.net/AMR.121-122.574
Citation
H. Y. Jiang, M. Dong, W. Li, "Application of BP Neural Network into the Kow of Chemical Contaminants", Advanced Materials Research, Vols. 121-122, pp. 574-578, 2010
Online since
June 2010
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Price
$32.00
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