Prediction of Wort Density with LSTM Network
<|reference_start|>Prediction of Wort Density with LSTM Network: Many physical target values in technical processes are error-prone, cumbersome, or expensive to measure automatically. One example of a physical target value is the wort density, which is an important value needed for beer production. This article introduces a system that helps the brewer measure wort density through sensors in order to reduce errors in manual data collection. Instead of a direct measurement of wort density, a method is developed that calculates the density from measured values acquired by inexpensive standard sensors such as pressure or temperature. The model behind the calculation is a neural network, known as LSTM.<|reference_end|>
@article{rembold2024prediction,
    title={Prediction of Wort Density with LSTM Network},
    author={Derk Rembold, Bernd Stauss, Stefan Schwarzkopf},
    journal={arXiv preprint arXiv:2403.06458},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.06458},
    primaryClass={cs.LG}
}