• DocumentCode
    2441756
  • Title

    Cloud Neural Network Algorithm Based on Cloud Transformation

  • Author

    Han Liwei ; Li Zongkun

  • Author_Institution
    Sch. of Water Conservancy & Environ. Eng., Zheng Zhou Univ., Zheng Zhou
  • fYear
    2008
  • fDate
    27-28 Dec. 2008
  • Firstpage
    237
  • Lastpage
    240
  • Abstract
    For the aim of improving the simulation ability of neural network and being able to reflect the randomness, fuzziness and the relevance between the two existed in the real world, a new algorithm-cloud neural network (CNN) based on cloud transformation is presented in this paper. And the parameter adjustment method of CNN is given. The CNN based on cloud transformation could be used in the nonlinear system simulation successfully. Simulation example shows that CNN has a faster convergence rate and higher convergence accuracy in calculation. At the same time, the CNN also has better generalization ability, which means it has a broad prospect on application.
  • Keywords
    generalisation (artificial intelligence); neural nets; nonlinear systems; simulation; cloud neural network algorithm convergence; cloud transformation theory; generalization ability; nonlinear system simulation; parameter adjustment method; Cellular neural networks; Clouds; Distribution functions; Entropy; Frequency; Fuzzy neural networks; Fuzzy reasoning; Helium; Neural networks; Uncertainty; Cloud neural network(CNN); Cloud transformation; Parameter adjustment; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling, Simulation and Optimization, 2008. WMSO '08. International Workshop on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-0-7695-3484-8
  • Type

    conf

  • DOI
    10.1109/WMSO.2008.103
  • Filename
    4756997