engleski

Selection of optimal training methodology for development of artificial neural network retention model in ion chromatography

The chromatographic property, which has the major impact on the separation quality, is retention. If there is a business expectation to find reasonable separation conditions within a couple of days, then there are only a dozen or so experiments possible before time runs out. Therefore, it is still important to try to apply different methodologies in order to increase predictive ability of retention in overall optimization process. Different training algorithms, activation function, number of hidden layer neurons and number of experimental data points used for training set were optimized until minimum on error surface has been found.

ion chromatography; optimal training methodology; artificial neural network; retention model

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