Cognitive Matching of Design Subjects in Product Form Evolutionary Design

感性 感性工学 计算机科学 认知 匹配(统计) 产品设计 人工智能 理想溶液 构造(python库) 产品(数学) 人机交互 数学 心理学 统计 物理 几何学 神经科学 热力学 程序设计语言
作者
Shutao Zhang,Shijie Wang,Aimin Zhou,Shifeng Liu,Jianning Su
出处
期刊:Computational Intelligence and Neuroscience [Hindawi Limited]
卷期号:2021: 1-23 被引量:6
标识
DOI:10.1155/2021/8456736
摘要

In actual product development, the cognitive differences between users and designers make it difficult for the designed products to be recognized by users. To reduce the cognitive differences between these two design subjects, this paper proposes a method of cognitive matching of the design subjects. First, we use the relevant methods of Kansei engineering to quantify the Kansei image cognition of the two design subjects and construct a cognitive matching model of the design subjects with information entropy and the technique for order preference by similarity to ideal solution (TOPSIS). Second, according to the Kansei image, the Kansei image prototype cluster is constructed, and the representative Kansei image prototype is obtained. Then, we combine an artificial neural network (ANN) with a cognitive matching model of the design subjects to construct a product Kansei image evaluation system; this is used to evaluate the evolved forms. Finally, a product Kansei image form evolution system is constructed based on the genetic algorithm (GA). To some extent, the system simulates the cognitive matching process between designers and users in product design, helps designers to more accurately understand the cognitive trends of the two design subjects, and provides a theoretical basis for the intelligent design of product forms through the cognitive balance of multiple design subjects. This paper takes a beverage bottle as an example to verify the feasibility of the model through a comparative study.
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