DocumentCode
2181462
Title
Research on Product Image Form Design Based on ANFIS
Author
Li, Yongfeng ; Zhu, Liping
Author_Institution
Coll. of Mech. & Electr. Eng., Xuzhou Normal Univ., Xuzhou, China
Volume
1
fYear
2010
fDate
29-31 Oct. 2010
Firstpage
119
Lastpage
122
Abstract
Product image form design, which focuses on customers´ psychological demands, is arousing attention increasingly. This paper presents a novel approach of customer-oriented design for translating customers´ kansei image into product design elements. The most influential form elements are identified through rough set theory. Based on this, the relationship between the key form elements and customers´ kansei is constructed by adaptive neuro-fuzzy inference system (ANFIS) using MATLAB. To validate the prediction performance of ANFIS, fuzzy logic and back propagation neural network models are utilized. An experimental study of glasses design is conducted based on the proposed method, and the results suggest that ANFIS has a good prediction performance.
Keywords
backpropagation; customer satisfaction; demand forecasting; design; fuzzy logic; fuzzy reasoning; production engineering computing; rough set theory; ANFIS; Matlab; adaptive neuro-fuzzy inference system; back propagation neural network; customer-oriented design; customers psychological demands; fuzzy logic; kansei image; product image form design; rough set theory; Adaptation model; Artificial neural networks; Firing; Fuzzy logic; Glass; Predictive models; Product design; ANFIS; glasses; kansei engineering; product design;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design (ISCID), 2010 International Symposium on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-8094-4
Type
conf
DOI
10.1109/ISCID.2010.46
Filename
5692678
Link To Document