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首页> 外文期刊>Journal of food engineering >Artificial neural network model with a culture database for prediction of acidification step in cheese production
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Artificial neural network model with a culture database for prediction of acidification step in cheese production

机译:带有培养数据库的人工神经网络模型可预测奶酪生产中的酸化步骤

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An artificial neural network with a culture database was developed to predict process behavior in cheese production. Based on the experimental investigations, it was found that the determination of the final process time of the acidification step, followed by rennet addition, is the key to successful operation of cheese processing. In order to determine the optimal timing for the rennet addition, it is practically useful to develop a model which can predict the final process time in the acidification process for successful cheese production. Therefore, an artificial neural network system with a culture database containing various operating data, in which the learning data for back propagation were selected from a culture database based on the Euclid distance, was examined. The system enabled successful prediction the final process time in the acidification process based on several operating data and the culture database.
机译:开发了带有培养数据库的人工神经网络,以预测奶酪生产中的过程行为。基于实验研究,发现确定酸化步骤的最终处理时间,然后添加凝乳酶,是成功进行奶酪加工的关键。为了确定加入凝乳酶的最佳时机,建立一个模型可以实际预测有用的模型,该模型可以预测酸化过程中的最终过程时间,以成功生产奶酪。因此,研究了具有包含各种操作数据的培养数据库的人工神经网络系统,其中基于欧几里得距离从培养数据库中选择了用于反向传播的学习数据。该系统能够基于多个操作数据和培养数据库成功预测酸化过程中的最终过程时间。

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