Abstract:
The purpose of this study was to develop an advanced investigation strategy for shelf life estimation of carbonated soft drinks. The strategy was based on the training capability of an Artificial Neural Networks and it has proves to be very successful. The model developed by using the Back-Propagation Neural Networks and simulations, was used to predict the variation in the CO2 content of carbonated soft drinks, bottled in PET containers.
Keywords:
soft drinks, Backpropagation Artificial Neural Netwoks, shelf life
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