基于BP神经网络和NSGA-II算法的交接盒的注塑成型过程参数的多目标优化

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A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars
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Tengjiao Hong1,2, Dong Huang1, Fengjuan Ding1

  • 1College of Intelligent Manufacturing, Anhui Science and Technology University, Chuzhou 233100, China.

Materials (Basel, Switzerland)
|February 13, 2025
PubMed
概括

这项研究利用BP神经网络和NSGA-II算法优化了塑料注塑成型质量. 该方法显著减少了塑料零件的体积收缩和曲面变形等缺陷.

关键词:
在BP神经网络中,神经网络交叉箱的交叉箱是一个交叉箱.多目标优化多目标优化过程参数 过程参数体积收缩率是指体积的收缩率.扭曲变形的变形变形变形的变形

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