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文章基本信息

  • 标题:Research on the Decision Model of Product Design Based on a Deep Residual Network
  • 本地全文:下载
  • 作者:Licheng Zong ; Nana Wang
  • 期刊名称:Scientific Programming
  • 印刷版ISSN:1058-9244
  • 出版年度:2022
  • 卷号:2022
  • DOI:10.1155/2022/8490683
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:An artificial intelligence (AI) design decision model is constructed to improve the efficiency of design decision evaluation and avoid the influence of the decision preference on product design and development. Using the concept of AI, the proposed model is based on a data set of product modeling design schemes, and the data set is marked with product modeling semantics. The deep learning residual network (ResNet) algorithm is used to train the data set to improve the accuracy of design decisions, transform the general design decision problem into the semantic recognition problem of design scheme images, and eliminate the design decision preference to the greatest extent. The validity and the feasibility of the proposed AI design decision-making method based on the ResNet algorithm are verified via an example of motorcycle modeling design decision-making.
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