Introduction to Grey system theory
The Journal of Grey System
Network Performance Assessment for Neurofuzzy Data Modelling
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
Evaluation of alternatives for product customization using fuzzy logic
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Form design of product image using grey relational analysis and neural network models
Computers and Operations Research
A neurofuzzy-evolutionary approach for product design
Integrated Computer-Aided Engineering
A Kansei mining system for affective design
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Nowadays customers choose products strictly in terms of their specific demands. How to quickly and accurately catch customers' feelings and transform them into design elements and vice versa becomes an important issue. This study explores the bi-directional relationship between customers' demands or needs and product forms by using a novel integral approach. High-price machine tools are used as our demonstration target. This integral approach adopts the ''grey system theory (GST)'', and the state-of-the-art machine learning based modeling formalism ''support vector regression (SVR)'' in the ''Kansei engineering (KE)'' process. The GST is used to effectively determine the influence weighting of form parameters on product images and the SVR is used to precisely establish the mapping relationship between product form elements and product images. Furthermore, for practical concerns, a user-friendly design hybrid design expert system was developed based on the proposed novel integral schemes.