DocumentCode
295873
Title
Coactive neuro-fuzzy modelling for colour recipe prediction
Author
Mizutani, Eiji ; Jang, Jyh-Shing R. ; Nishio, Kcnichi ; Takagi, Hideyuki ; Anslander, D.M.
Author_Institution
Inf. Syst. Dept., Kansai Paint Co. Ltd., Osaka, Japan
Volume
5
fYear
1995
fDate
Nov/Dec 1995
Firstpage
2252
Abstract
Explores neuro-fuzzy approaches to computerized colour recipe prediction which relates surface spectral reflectance of a target colour to several colorant proportions. The approaches are expressed within the framework of CANFIS (co-active neuro-fuzzy inference system) where both neural networks (NNs) and fuzzy systems (FSs) play active roles together in pursuit of a given task. To find an ideal adaptive model for this problem, the authors have investigated a variety of structures, they feature knowledge-embedded architectures and an adaptive FS, which serves to determine colour selection. They have enormous potential for augmenting prediction capability
Keywords
colour; fuzzy systems; knowledge based systems; neural nets; reflectivity; CANFIS; coactive neuro-fuzzy modelling; colorant proportions; colour recipe prediction; colour selection; knowledge-embedded architectures; surface spectral reflectance; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487712
Filename
487712
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