基于感性工學的兒童自行車造型優選設計研究
摘 要：為改善兒童自行車的同質化現象，文章通過感性工學理論研究符合兒童和家長情感需求的兒童自行車造型。首先，利用在線評論數據和聚類分析確定代表性樣本和造型設計元素，運用語義差異法和因子分析獲取和分析感性意象評價值；其次，通過GA-BP神經網絡構建感性意象和造型設計元素之間的映射模型，預測目標感性意象的最優造型設計元素組合；最后，進行造型優選設計實踐。結果顯示感性工學利用在線評論數據能有效獲取用戶的情感需求， GA-BP神經網絡可準確建立造型設計元素和感性意象之間的映射關系，為兒童自行車造型優選設計提供指導。
關鍵詞：工業設計；兒童自行車；感性工學；GA-BP神經網絡；在線評論
中圖分類號：TB472 文獻標識碼：A 文章編號：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
