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Application of Optimization Algorithms in Injection Molding Process Parameters

机译:优化算法在注塑成型工艺参数中的应用

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The data of process parameters and quality index from CAE simulation orthogonal test is used as training samples, the BP neural network is trained and the neural networks ensemble approximate calculation agent model of the relations between processing parameters and the quality index of product are obtained. The agent model with a clear mathematical formula calculates quickly and accurately, so it can optimize globally by the genetic algorithm. The best group of process parameters is obtained and a multi-objective optimization of the quality index of products is realized.
机译:从CAE模拟正交测试的过程参数和质量指数的数据用作训练样本,获得了BP神经网络的训练,并且获得了处理参数与产品质量指标之间的关系的神经网络集合近似计算代理模型。具有清晰的数学公式的代理模型快速准确地计算,因此它可以通过遗传算法全球优化。获得了最佳的过程参数,并实现了产品质量指标的多目标优化。

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