Artificial neural network implementation for pbkp_rediction of beer taste quality

Abstract:

Brewing beer involves a number of steps to produce this popular alcoholic drink. Nowadays, the brewing industry has improved the techniques by automating most of the processes where usually humans use to take decisions. However, in small-scale breweries, the process is still been monitored and controlled by humans. One of the most important parts is the Sensory Panel test. This involves a human measurement of the quality of the beer in each batch produced. This information is useful for the brewers who can make decisions based in this analysis. This testing is very subjective and difficult to reproduce since it depends only on the panellist impression and experience. Artificial Neural Networks (ANN) are computational models, which can accurately pbkp_redict, classify and organize database on mathematical algorithms. They have been developed and used since 1943. As a result, today many industries have adopted this method to improve the process in different areas. For instance, human decisions making, which involves many subjective aspects, is one of the areas where ANN have the best potential of application. ANNs work similarly as the brain, simulating the neurons synapsis and the way they compute information. ANNs and their ability to learn is what makes this new tendency very popular worldwide.

Año de publicación:

2015

Keywords:

Fuente:

google