IEEE Access (Jan 2023)

Optimization Design of Product Form Driven by Image Cognitive Friction

  • Jinyan Ouyang,
  • Lingwan Huang,
  • Rui Zhang,
  • Jian Ma,
  • Jianning Su,
  • Shutao Zhang,
  • Aimin Zhou

DOI
https://doi.org/10.1109/ACCESS.2023.3329810
Journal volume & issue
Vol. 11
pp. 124278 – 124294

Abstract

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To balance the image cognitive friction of users and designers regarding product form, based on noncooperative game theory, a product form optimization design method was proposed to generate product forms that meet the common expectations of users and designers. First, the semantic difference method was used to construct the image cognitive spaces of users and designers. Second, based on the theory of computational aesthetics, production rules were used to structurally describe the aesthetic knowledge of product form; the aesthetic index values of product form were calculated; and two gray-box image evaluation models of design features, aesthetic indexes, and images were established with the method of quadratic polynomial stepwise regression. Finally, using the image cognitions of users and designers as game participants and the two image evaluation models as profit functions, a noncooperative game model was established, and a quantum genetic algorithm was used to obtain the Nash equilibrium solution of the model to achieve the optimal design of the product form. Taking the optimal design of a sphygmomanometer as an example, the rationality and effectiveness of the method are verified.

Keywords