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Research Article

Neural Network Prediction of the Solvatochromic Polarity/Polarizability Parameter

Daniel Svozil and Jiří G. K Šev

ík*

Department of Analytical Chemistry, Faculty of Science, Charles University, Albertov 2030, Prague CZ-128 40, Czech Republic

Vladimír Kvasni

Department of Mathematics, Faculty of Chemical Technology, Slovak Technical University, Bratislava SK-81 237, Slovakia

J. Chem. Inf. Comput. Sci., 1997, 37 (2), pp 338–342

DOI: 10.1021/ci960347e

Publication Date (Web): March 24, 1997

In papers with more than one author, the asterisk indicates the name of the author to whom inquiries about the paper should be addressed.

Abstract

A three-layer feed-forward neural network was used for the prediction of the polarity/polarizability parameter . A simulated annealing algorithm was used to minimize the error at the neural network output. Descriptors related to the structure of the compounds were calculated as the input vector. The Kohonen neural network was used to split the data set into training and testing sets. The results obtained from the neural network were compared with the MLRA results.