Predicting Ethanol Concentration in Industrial Sugarcane Fermentation Based on Knowledge Discovery in Databases

[摘要] At the present time, the amount of data stored in the sugar and alcohol industries is considered extensive and continuous. In the production of sugar and alcohol, stored information is not always analyzed. This is due to the amount of data, the diversity of sectors in the production process, along with the difficulty in knowing whether such data can be considered valid for any kind of analysis. This work proposes the use of the Knowledge Discovery in Databases (KDD) as an alternative tool for applying data from manufacturing process pertinent to the sugar and alcohol industries. The experiments were conducted with real data obtained from fermentation process during the harvest period. The contribution of this work is the identification of a KDD based on a knowledge structure, which can be used for prediction and simulation activities from the sugar and alcohol production process.

[学科分类] 自动化工程

[关键词] KDD ;Sugar and alcohol production ;Fermentation process ;Process optimization