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 :
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