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Modeling of Grey Neural Network and Its Applications

  • Jingling Yuan
  • Luo Zhong
  • Xiaoyan Li
  • Jie Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5370)

Abstract

Grey neural network is an innovative intelligent computing approach combing grey system model and neural network, which makes full use of the similarities and complementarity between grey system model and neural network to settle the disadvantage of applying Grey model and Neural Network separately. Some optimization algorithms such as genetic algorithm are also employed to modeling and optimizaion of grey neural network. Many typical grey neural work models such as GNNM(1,1),GRBF,DGRBF, GA-GRBF and so on are proposed and applied in this paper. A lot of comparative experimental results show that grey neural network models are capable of predicting a small sample of data accurately, easily and conveniently. The key technologies, research hotspots, difficulties and further development of grey neural network are discussed in this paper.

Keywords

Neural Network Grey Model Grey System Grey System Theory Uncertain Differential Equation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jingling Yuan
    • 1
  • Luo Zhong
    • 1
  • Xiaoyan Li
    • 1
  • Jie Li
    • 1
  1. 1.Computer Science and Technology SchoolWuhan University of TechnologyWuhanChina

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