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
Link To Document :
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