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A New Classification Method for Predicting the Output of Dye Process in Textile Industry by Using Artificial Neural Networks

机译:用人工神经网络预测纺织业染料过程产量的新分类方法

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In this paper, a new approach is proposed which predicts the output of the dyeing process in textile industry by using input data consisting of the alarms and/or the interventions during the process. Back-propagation algorithms and radial basis functions are utilized to form the neural networks in predicting whether the dye process is carried out correctly or not before an operator checks it manually. Industrial data are used to test the efficiency of the proposed concept which demonstrates that the success rate is over 85%.
机译:在本文中,提出了一种新方法,其通过使用在过程中由警报和/或干预措施组成的输入数据来预测纺织工业中的染色过程的输出。在操作员手动检查之前,利用反向传播算法和径向基函数来形成神经网络,以预测染料过程是否正确执行。工业数据用于测试所提出的概念的效率,表明成功率超过85%。

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