# Prediction of Wort Density with LSTM Network

arXiv: https://arxiv.org/abs/2403.06458 · HTML: https://mlsanity.com/paper/2403.06458/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 11 Mar 2024.

## Abstract (arXiv)

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.