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

机译:基于神经网络理论分析熔喷非织造型空气过滤效率的新预测

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摘要

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,用于预测从加工参数吹出熔体的空气过滤效率。本文采用了具有良好近似能力和快速收敛速率的径向基神经网络。结果表明,人工神经网络模型产生更准确和稳定的预测,并具有自适应识别的强大能力,这表明人工神经网络模型真的是一种有效且可行的建模方法。

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