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In order to predict percolation temperature of AOT-Based microemulsions (AOT/iC8/H2O w/o microemulsions) in the presence of small organic molecules (ureas and thioureas), different Artificial Neural Network architectures (ANN) have been carried out using a Perceptron Multilayer Artificial Neural Network with three entrance variables (W = value of the microemulsion, additive concentration, logP value). Best ANN architecture consists in three input neurons, one middle layer (with two neurons) and one output neuron. Correlation values were R = 0.9251 for the training set and R = 0.9719 for the prediction set.
From Iago Antonio Montoya | Gonzalo Astray | Antonio Cid | José Antonio Manso | Oscar Adrían Moldes | Juan Carlos Mejuto
(Received 30.01.2012; revised 30.03.2012)
Appeared in Tenside Surfactants Detergents 2012/04, Page 316-320
Direct link: http://www.tsd-journal.com/TS110197
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