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Updated: May 28, 2025

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars
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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

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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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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