DocumentCode
2587806
Title
Customer satisfaction assessment through a fuzzy neural controller
Author
Kuo, Ying-Feng ; Temponi, Cecilia ; Corley, H.W.
Author_Institution
Dept. of Ind. & Manuf. Syst. Eng., Texas Univ., Arlington, TX, USA
fYear
1996
fDate
19-22 Jun 1996
Firstpage
195
Lastpage
199
Abstract
Customer satisfaction measurement is an important part of marketing research in industrial organizations since it is the key to formulating customer value strategies and to continuously improving implementation of these strategies. We propose a general fuzzy neural network with back propagation learning for control tasks. The controller will measure customer satisfaction level for assessing advanced customer satisfaction strategies. This model is capable of tuning the membership function parameters and fuzzy IF-THEN rules simultaneously. The preliminary results presented in the research are promising and have opened new paths for future research
Keywords
backpropagation; fuzzy control; fuzzy neural nets; fuzzy set theory; marketing data processing; advanced customer satisfaction strategies; back propagation learning; customer satisfaction assessment; customer satisfaction level; customer value strategies; fuzzy IF-THEN rules; fuzzy neural controller; general fuzzy neural network; industrial organizations; marketing research; membership function parameters; Artificial neural networks; Biological neural networks; Customer satisfaction; Electrical equipment industry; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Fuzzy systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conference of the North American
Conference_Location
Berkeley, CA
Print_ISBN
0-7803-3225-3
Type
conf
DOI
10.1109/NAFIPS.1996.534730
Filename
534730
Link To Document