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人工神经网络与材料工艺的优化 被引量:3

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摘要 应用人工神经网络建立 7151铝合金的性能预测模型 ;在此基础上采用遗传算法对其工艺进行优化 ,获得了满意的结果 。
作者 董敏
机构地区 铁岭师专
出处 《辽宁师专学报(自然科学版)》 2000年第3期100-103,共4页 Journal of Liaoning Normal College(Natural Science Edition)
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共引文献16

同被引文献39

  • 1张乐福,谢长生,张以增.人工神经网络在材料实验数据处理中的应用[J].材料科学与工艺,1997,5(1):28-31. 被引量:18
  • 2QI Le Hua, HOU Jun Jie, CUI Pei Ling et al. Research on Prediction of the Processing Parameters of Liquid Extrusion by BP Network [ J ]. Journal of Materials Processing Technology, 1999,95 : 232 - 237.
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  • 6WANG X Y, SONG H, QIU G Z, et al. Prediction of superconductivity for oxides based on structural parameters and artificial neural network method [J]. Journal of Materials Processing Technology, 2000,10(4): 435 -438.
  • 7ZHANG Z, FRIEDRICH K, VELTEN K. Prediction on tribological properties of short fibre composites using artifical neural networks [ J ]. Wear, 2002,252: 668-675.
  • 8KORCZAK P, DYJA H, LABUDA E. Using neural network models for predicting mechanical properties after hot plate rolling processes [ J]. Journal of Materials Processing Technology, 1998,80 - 81: 481 - 486.
  • 9LI M Q, XIONGA M,HUANGW C, et al. Microstructural evolution and modelling of the hot compression of a TC6 Titanium alloy [ J]. Materials Characterization. 2003,49: 203 - 209.
  • 10SONG R G, ZHANG Q Z. Heat treatment technique optimization for 7175 Aluminum alloy by an artificial neural network and a genetic algorithm [ J ]. Journal of Materials Processing technology, 2001,117: 84 - 88.

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