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Using Artificial Neural Network Model on Studying Fiber Diameter of Spunbonding Nonwovens:Comparison with Mathematical Empirical Statistical Method Model

机译:用人工神经网络模型研究纺粘非织造布的纤维直径:与数学经验统计方法模型的比较

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In this article, the mathematical statistical model and artificial neural network model are established and used to predict the fiber diameter of spunbonding nonwovens. The artificial neural network model has good approximation capability and fast convergence rate, and is employed in this research.The results show it can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the mathematical statistical model, which shows that the artificial neural network technique is really an effective and viable modeling method when the required number of experimental data sets is available.The effects of process parameters on fiber diameter are also determined by the ANN model. By analyzing the results of the mathematical statistical model, the effects of process parameters on fiber diameter can be predicted.
机译:本文建立了数学统计模型和人工神经网络模型,并用于预测纺粘非织造布的纤维直径。人工神经网络模型具有良好的逼近能力和较高的收敛速度,在本研究中得到了应用。结果表明,该模型可以提供纤维直径的定量预测,并且比数学统计模型可以提供更准确,更稳定的预测,这表明当所需数量的实验数据集可用时,神经网络技术确实是一种有效可行的建模方法。过程参数对纤维直径的影响也由ANN模型确定。通过分析数学统计模型的结果,可以预测工艺参数对纤维直径的影响。

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