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- W2620256326 abstract "Abstract In order to apply a model based control strategy such as flexible recipes control to an industrial batch process, a model of the process dynamics is needed. This paper presents the modelling procedure for two such models: a semi-empirical and an artificial neural network model. Both models predict precipitation rates of TiO 2 particles in an industrial hydrolysis process. Model properties and their prediction accuracy is compared. The artificial neural network is trained using the augmented training data set approach. A simulator has been designed to study the application Of flexible recipe instructions." @default.
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- W2620256326 date "1998-06-01" @default.
- W2620256326 modified "2023-10-18" @default.
- W2620256326 title "A Semi-Empirical and a Neural Network Model of a Batch Plant Dynamics for Flexible Recipes Control" @default.
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- W2620256326 doi "https://doi.org/10.1016/s1474-6670(17)44943-3" @default.
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