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基于语义的产品自适应混合免疫遗传形态设计

宋红 余隋怀 耶琳 赵明磊

宋红, 余隋怀, 耶琳, 赵明磊. 基于语义的产品自适应混合免疫遗传形态设计[J]. 机械科学与技术, 2014, 33(11): 1627-1632. doi: 10.13433/j.cnki.1003-8728.2014.1104
引用本文: 宋红, 余隋怀, 耶琳, 赵明磊. 基于语义的产品自适应混合免疫遗传形态设计[J]. 机械科学与技术, 2014, 33(11): 1627-1632. doi: 10.13433/j.cnki.1003-8728.2014.1104
Song Hong, Yu Suihuai, Ye Lin, Zhao Minglei. A Semantic-based Adaptive Hybrid Immune Product Shape Design Method[J]. Mechanical Science and Technology for Aerospace Engineering, 2014, 33(11): 1627-1632. doi: 10.13433/j.cnki.1003-8728.2014.1104
Citation: Song Hong, Yu Suihuai, Ye Lin, Zhao Minglei. A Semantic-based Adaptive Hybrid Immune Product Shape Design Method[J]. Mechanical Science and Technology for Aerospace Engineering, 2014, 33(11): 1627-1632. doi: 10.13433/j.cnki.1003-8728.2014.1104

基于语义的产品自适应混合免疫遗传形态设计

doi: 10.13433/j.cnki.1003-8728.2014.1104
基金项目: 

国家自然科学基金项目(51105310)资助

详细信息
    作者简介:

    宋红(1977- ),博士研究生,研究方向为数字媒体艺术设计和计算机辅助工业设计(CA1D),hsong@xsyu.edu.cn。

    通讯作者:

    余隋怀,教授,博士生导师,ysuihuai@vip.sina.com.

A Semantic-based Adaptive Hybrid Immune Product Shape Design Method

  • 摘要: 为进一步探讨产品设计中形态特征和用户情感匹配的问题,提出了一种基于语义的自适应混合免疫遗传产品形态设计优化方法.通过目标语义的模糊隶属度的匹配来生成初始抗体集合,再利用专家建议来生成疫苗集合,并在演化过程中通过疫苗接种和基于亲和度的选择来加速收敛并保持种群多样性,利用反向传播神经网络(BPNN)将形态特征语义空间映射到情感语义空间并构造适应度函数.此外,疫苗接种概率按接种效果进行自适应调节,并基于信息熵理论定义抗体之间的亲合度及抗体的选择概率.原型系统实现了形态设计的快速生成和设计评价,验证了方法的有效性.
  • [1] Sevaux M,Mineur Y. A curve-fitting genetic: algorithmfor a styling application[J]European Journal of Operational Research,2007,179(3):895-905
    [2] Li Y F,Zhu L P. Research on producta image formoptimization design[C]//Computer Seience andInforniation Technology. IEEE International Conference onComputer Seience and Inforniation Technology, 2010;9-11,2010,IEEE,2010}173-177
    [3] Hsiao SW,Chiua F Y, Lua S H. Producta-form designmodel based on genetic: algorithms[J]InternationalJournal of Industrial Ergonomic、,2010,40(3);237-246
    [4] Heermann P D, Khazenie N. Classification of multispectaralremote sensing data using a back-propagation neuralnetwork[J]IEEE Trans. on Geoseience and RemoteSensing,1992,30(1):81-88
    [5] Goldberg D E. Genetic: algorithms in search, optimization,and machine learning[M]New Jersey:Addison-Wesley,1989
    [6] Song H,Zhang D,Liu J. An adaptive hybrid immunegenetic: algorithm for maximum cut problem[J]. LectaureNotes in Computer Seience,2005:863-866
    [7] Jiao L C,Wang L. A novel genetic: algorithm based onimmunity[J]IEEE Trans. on Systems,Man andCybernetic、,2000,30(5);552-561
    [8] Chun J S, Kim M K, Jung H K, et al. Shape optinuzationof electaromagnetic devices using immune algorithm[J]IEEE Trans. on Magnetic,1997,33(2):1976-1879
    [9] Srinivas M, Patnaik L M. Adaptive probabilities of crossoverand mutations in gas[J]. IEEE Trans. on Systems,Manand Cybernetic、,1994,24(4);493-530
    [10] 徐江,孙守迁基于正交-交互式遗传算法的产品形态设计[J]计算机集成制造系统,2007,13(8);1470-1475Xu J,Sun S Q. Producta form design based onorthogonal interactaive genetic: algorithm[J]ComputerIntegrated Manufactauring Systems,2007,13(8):1470-1475(in Chinese)
    [11] Zwicky F, Invention D. Research through the morphologicalapproach[J]New Methods of Thought and Procedure,1967:273-297"
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出版历程
  • 收稿日期:  2013-03-11

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