文献类型：期刊文献

英文题名：Constructing a MOEA approach for product form Kansei design based on text mining and BPNN

作者：Wang, Tianxiong[1]; Xu, Mengmeng[1]; Yang, Liu[2]; Zhou, Meiyu[3]; Sun, Xin[3]

机构：[1] School of Art, Anhui University, Hefei, China; [2] School of Machinery and Electrical Engineering, Anhui Jianzhu University, Hefei, China; [3] School of Art Design and Media, East China University of Science and Technology, Shanghai, China

年份：2024

卷号：46

期号：4

起止页码：8865

外文期刊名：Journal of Intelligent and Fuzzy Systems

收录：EI(收录号：20242116135606)

语种：英文

外文关键词：Backpropagation - Data mining - Genetic algorithms - Inverse problems - Iterative methods - Neural networks - Pareto principle - Product design - Text processing - Torsional stress

摘要：Kansei Engineering (KE) is a product design method that aims to develop products to meet users' emotional preferences. However, traditional KE faces the problem that the acquisition of Kansei factors does not represent the real consumers demands based on manual and reports, and using traditional methods to calculate relationship between Kansei factors and specific design elements, which can lead to the omission of key information. To address these problems, this study adopts text mining and backward propagation neural networks (BPNN) to propose a product form design method from a multi-objective optimization perspective. Firstly, Term Frequency-Inverse Document Frequency (TF-IDF) and WordNet are used to extract key user Kansei requirements from online review texts to obtain more accurate Kansei knowledge. Secondly, the BPNN is used to establish the non-linear relationship between product Kansei factors and specific design elements, and a preference mapping prediction model is constructed. Finally, BPNN is transformed into an iterative prediction value of non-dominated sorting genetic algorithm-II (NSGA-II), and the model is solved through multi-objective evolutionary algorithm (MOEA) to obtain the Pareto optimal solution set that satisfies the user's multiple emotional needs, and the fuzzy Delphi method is used to obtain the best product form design scheme that meets the user's multiple emotional images. Using the example of electric bicycle form design could show that this proposed method can effectively complete multi-objective product solutions innovation design. ? 2024 - IOS Press. All rights reserved.