基于遗传算法的人工神经网络对增韧尼龙冲击性能的预测  

Prediction of Impact Property to the Toughening Nylon of Nerve Network based on Genetic Algorithm

作　　者：陈坤[1] 宋克东[1] 张瑜[1] 田祥儒[1] 陈如意[1] 

机构地区：[1]株洲时代新材料科技股份有限公司,湖南株洲412007

出　　处：《塑料工业》2012年第1期111-114,共4页China Plastics Industry

摘　　要：采用基于遗传算法的人工神经网络预测了马来酸酐接枝乙烯-辛烯共聚物(POE-g-MAH)/线型低密度聚乙烯(LLDPE)对尼龙6(PA6)冲击性能的影响,探索了基于遗传算法的人工神经网络在高分子复合材料研究中的应用途径。结果表明:基于遗传算法的人工神经网络能够很好地预测高分子复合材料的性能;当POE-g-MAH和LLDPE的含量分别为12%和8%时,PA6的冲击强度达到94.12 kJ/m2。The effect of POE-g-MAH/LLDPE on the impact properties of PA6 was predicted neural net- work based on genetic algorithm, and neural network based on genetic algorithm applied to the research of polymer composites was studied. The results showed that neural network based on genetic algorithm was a very effective method in prediction of the property of the polymer composites. The impact strength of the toughened nylon 6 reached 94. 12 kJ/m2 when the content of POE-g-MAH was 12 wt% and LLDPE was 8 wt%.

关 键 词：遗传算法 神经网络 尼龙6 线型低密度聚乙烯 

分 类 号：TQ323.6[化学工程—合成树脂塑料工业] TQ325.12