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A new prediction based on neural network theory analysis air filtration efficiency of the melt blowing nonwovens

机译:基于神经网络理论的熔纺非织造布空气过滤效率的新预测

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In this work, the three layers of artificial neural network model is established for predicting the air filtration efficieny of melt blowing from the processing parameters. The radial basis neural network, which has good approximation capability and fast convergence rate, is employed in this paper. The results show that the artificial neural network model produces more accurate and stable predictions and has strongly capability of self-adaptive recognition, which shows that the artificial neural network model is really an effective and viable modeling method.
机译:在这项工作中,建立了三层人工神经网络模型,用于根据工艺参数预测熔喷的空气过滤效率。本文采用了具有良好的逼近能力和收敛速度快的径向基神经网络。结果表明,人工神经网络模型能够产生更准确,更稳定的预测结果,具有很强的自适应识别能力,说明人工神经网络模型确实是一种有效可行的建模方法。

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