基于感性工学的儿童自行车造型优选设计研究
摘 要：为改善儿童自行车的同质化现象，文章通过感性工学理论研究符合儿童和家长情感需求的儿童自行车造型。首先，利用在线评论数据和聚类分析确定代表性样本和造型设计元素，运用语义差异法和因子分析获取和分析感性意象评价值；其次，通过GA-BP神经网络构建感性意象和造型设计元素之间的映射模型，预测目标感性意象的最优造型设计元素组合；最后，进行造型优选设计实践。结果显示感性工学利用在线评论数据能有效获取用户的情感需求， GA-BP神经网络可准确建立造型设计元素和感性意象之间的映射关系，为儿童自行车造型优选设计提供指导。
关键词：工业设计；儿童自行车；感性工学；GA-BP神经网络；在线评论
中图分类号：TB472 文献标识码：A 文章编号：1672-7053(2024)03-0080-05
Abstract：In order to improve the homogeneity of children's bicycles, this paper studies the models of children's bicycles that meet the emotional needs of children and parents are studied through the theory of Kansei engineering. Firstly, online comment data and cluster analysis were used to determine the representative samples and design elements; The semantic difference method and factor analysis were used to obtain and analyze the perceptual image evaluation value. Secondly, GA-BP neural network is used to build a mapping model between perceptual image and modeling design elements, and predict the optimal combination of modeling design elements of the target perceptual image, and finally carry out the modeling optimization design practice. The results show that Kansei engineering can effectively obtain users' emotional needs by using online comment data, and GA-BP neural network can accurately establish the mapping relationship between design elements and perceptual images, providing guidance for the optimal design of children's bicycle modeling.
Key Words：Industrial Design; Children's Bicycles; Kansei Engineering; GA-BP Neural Network; Online Comment
