All Issue

2018 Vol.43, Issue 3 Preview Page
September 2018. pp. 229-236
Abstract

Purpose: Makgeolli is a traditional alcoholic beverage made from rice with a fermentation starter called “nuruk.” The concentration of alcohol in makgeolli depends on the temperature of the fermentation tank. It is important to monitor the alcohol concentration to manage the makgeolli production process. Methods: Data were collected from 84 makgeolli fermentation tanks over a year period. Independent variables included the temperatures of the tanks and the room where the tanks were located, as well as the quantity, acidity, and water concentration of the source. Software for the multilayer perceptron model (MLP) was written in Python using the Scikit-learn library. Results: Many models were created for which the optimization converged within 100 iterations, and their coefficients of determination R2 were considerably high. The coefficient of determination R2 of the best model with the training set and the test set were 0.94 and 0.93, respectively. The fact that the difference between them was very small indicated that the model was not overfitted. The maximum and minimum error was approximately 2% and the total MSE was 0.078%. Conclusions: The MLP model could help predict the alcohol concentration and to control the production process of makgeolli. In future research, the optimization of the production process will be studied based on the model.

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Information
  • Publisher :The Korean Society for Agricultural Machinery
  • Publisher(Ko) :한국농업기계학회
  • Journal Title :Journal of Biosystems Engineering
  • Journal Title(Ko) :바이오시스템공학
  • Volume : 43
  • No :3
  • Pages :229-236
  • Received Date :2018. 07. 24
  • Accepted Date : 2018. 08. 23