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Modelling and optimisation control of polymer composite moulding processes using bootstrap aggregated neural network models

机译:使用Bootstrap聚合神经网络模型的聚合物复合成型工艺建模与优化控制。

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This paper presents using bootstrap aggregated neural networks for the modelling and optimization control of reactive polymer composite moulding processes. Neural network models for the degree of cure are developed from process operational data. To improve model generalization capability, multiple neural networks are developed from bootstrap re-samples of the original data and are combined. Optimal heating profile is obtained by solving an optimization problem using the neural network model. The proposed method is applied to both simulated data and real industrial data.
机译:本文介绍了使用自举聚合神经网络进行反应性聚合物复合材料成型过程的建模和优化控制。从过程操作数据中开发了用于固化程度的神经网络模型。为了提高模型泛化能力,从原始数据的bootstrap重采样中开发了多个神经网络,并将它们组合在一起。通过使用神经网络模型解决优化问题,可以获得最佳加热曲线。所提出的方法既适用于模拟数据,又适用于实际工业数据。

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