The prediction of the substantivity of anionic, water soluble dyes on a biomass using neural networks

Abstract

The substantivity of series of anionic, water soluble dyes for a biomass has been measured. Using feed-forward back propagation neural networks and relatively simple empirical and semi-empirical molecular descriptors as input variables, the correlation between the predicted substantivity and the observed substantivity was determined. Depending on the molecular descriptors used as input variables and the number of hidden layers in the neural network the correlation between the predicted substantivity and the observed substantivity was 0.80 and 0.76.