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Prediction of air-jet textured yarn properties using statistical method and neural network

机译:用统计方法和神经网络预测喷气变形纱的性能

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摘要

Artificial neural network has been used for predicting the air-jet textured yarn properties and the performance of ANN model has been compared with the statistical model based on Box-Behnken response surface design. Leaving apart some stray cases, the artificial neural network is able to predict the properties with reasonably low prediction error. Prediction ability of the network is better for the instability and physical bulk property as compared to tenacity. For the set of data used for constructing the network, the mean square errors are comparatively higher in the neural network model than the regression model.
机译:人工神经网络已被用于预测喷气变形纱的性能,并将ANN模型的性能与基于Box-Behnken响应面设计的统计模型进行了比较。撇开一些零散的案例,人工神经网络能够以较低的预测误差来预测属性。与韧性相比,网络的预测能力对于不稳定性和物理体积特性更好。对于用于构建网络的数据集,神经网络模型中的均方误差相对高于回归模型。

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