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Author:

Wang, Minjie (Wang, Minjie.) | Wang, Min (Wang, Min.) (Scholars:王民) | Zan, Tao (Zan, Tao.)

Indexed by:

EI Scopus

Abstract:

It is a comprehensive problem to accurately set the ink key opening of every ink zone for a specific press according to the color coverage of the graphical content which will be printed on the sheet. In this paper, a new-type neural network is proposed to preset the key opening of the ink zones, which combines the fuzzy ART neural network and BP neural network, and is with the capability of half-incremental learning and good generalization. The actual qualified printed sheets are used as training samples to train fuzzy ART-BP network, so that the nonlinear mapping relationship among graphic digital information, printing conditions, and ink key control parameters is established. The experimental results indicate that the fuzzy ART-BP network algorithm could effectively shorten adjusting time of the ink key setting and improve printing efficiency. © 2013 Springer-Verlag.

Keyword:

Fuzzy neural networks Fuzzy logic Arts computing Fuzzy inference

Author Community:

  • [ 1 ] [Wang, Minjie]School of Mechatronical Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Wang, Min]School of Mechatronical Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Zan, Tao]School of Mechatronical Engineering, Beijing University of Technology, Beijing 100124, China

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Source :

ISSN: 1876-1100

Year: 2013

Issue: VOL. 3

Volume: 218 LNEE

Page: 759-764

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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