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

机译:基于知识发现在数据库中的工业甘蔗发酵中预测乙醇浓度

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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.
机译:目前,储存在糖和酒精行业中的数据量被认为是广泛的和连续的。 在糖和酒精的生产中,并不总是分析存储的信息。 这是由于数据量,生产过程中的部门的多样性,以及了解这些数据是否可以被认为是有效的任何类型的分析。 这项工作提出使用数据库(KDD)中的知识发现作为应用与糖和酒精工业相关的制造过程中数据的替代工具。 通过在收获期间用从发酵过程中获得的真实数据进行实验。 这项工作的贡献是基于知识结构识别KDD,可用于来自糖和酒精生产过程的预测和仿真活动。

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