Spray deposition with following continuous extrusion (SD-CE) forming technique is a novel technology that combines spray forming and continuous extrusion. Optimization of test parameters for spray deposition is an important part of SD-CE. In this study, Al-20Si alloy was produced by spray forming at different melt temperature and gas pressure, and obtained grain diameter of 8 group primary silicon phase. Based on the experimental results, an Artificial Neural Network (ANN) with single hidden layers composing of 10 neurons was employed to simulate optimizing of test parameters for spray deposition. The inputs of the model are melt temperature and gas pressure. The output of the model is grain diameter. Finally, the minimum relative error of grain diameter is 0.09%, the maximum relative error is 8.38%, and error majority concentrate within 3.80%, the average absolute relative error(AARE) is 1.04%, R is 0.097, the error is small. The optimal test parameters for spray deposition are...

中文翻译：

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基于人工神经网络的铝合金约束喷射成形试验参数优化。

跟随连续挤压（SD-CE）成型技术的喷涂沉积是一种结合喷涂成型和连续挤压的新颖技术。喷射沉积测试参数的优化是SD-CE的重要组成部分。本研究通过在不同的熔体温度和气压下通过喷射成型制备Al-20Si合金，并获得了8族初级硅相的粒径。根据实验结果，采用由10个神经元组成的单隐藏层的人工神经网络（ANN）模拟喷雾沉积测试参数的优化。该模型的输入是熔体温度和气压。模型的输出是晶粒直径。最后，晶粒直径的最小相对误差为0.09％，最大相对误差为8.38％，误差多数集中在3.80％以内，平均绝对相对误差（AARE）为1.04％，R为0.097，误差很小。喷雾沉积的最佳测试参数为...