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The Artificial Neural Network and Regression Analysis Approach to Prediction of the Fiber Diameter of Spunbonding Fabrics

机译:人工神经网络和回归分析方法预测纺粘织物的纤维直径

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In this work, the artificial neural network model and statistical regression model are established and utilized for predicting the fiber diameter of spunbonding nonwovens from the process parameters. The artificial neural network model has good approximation capability and fast convergence rate, which is used in this research. The results show the artificial neural network model can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the statistical regression model, which reveals that the artificial neural network model is based on the inherent principles, and it can yield reasonably good prediction results and provide insight into the relationship between process parameters and fiber diameter.
机译:在这项工作中,建立了人工神经网络模型和统计回归模型,并用于预测来自工艺参数的纺粘非织造布的纤维直径。人工神经网络模型具有良好的近似能力和快速收敛速率,用于本研究。结果表明人工神经网络模型可以提供比统计回归模型的纤维直径的定量预测,并产生比统计回归模型更准确和稳定的预测,这揭示了人工神经网络模型基于固有原理,并且它可以产生合理的预测结果并提供洞察过程参数与纤维直径之间的关系。

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