National Changhua University of Education Institutional Repository : Item 987654321/13787
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题名: Design of Optimization Parameters with Hybrid Genetic Algorithm Method in Multi-Cavity Injection Molding Process
作者: Chen, Wen-Jong;Lin, Jia-Ru
贡献者: 工業教育與技術學系
关键词: Artificial Neural Network (ANN);Traditional Genetic Algorithm;Warpage
日期: 2012-02
上传时间: 2012-08-27T10:55:38Z
出版者: Trans Tech Publications, Switzerland.
摘要: This paper combines an artificial neural network (ANN) with a traditional genetic algorithm (GA) method, called hybrid genetic algorithm (HGA), to analyze the warpage of multi-cavity plastic injection molding parts. Simulation results indicate that the minimum and the maximum warpage of the hybrid genetic algorithm (HGA) method were lower than that of the traditional GA method and CAE simulation. These results reveal that, when HGA is applied to multi-cavity plastic warpage analysis, the optimal process conditions are significantly better than those using the traditional GA method or CAE simulation.
關聯: Advanced Materials Research, 463-464: 587-591
显示于类别:[工業教育與技術學系] 期刊論文

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