• DocumentCode
    2903679
  • Title

    A new growing self-organizing neuron-fuzzy network with application to wastewater treatment

  • Author

    Jun-fei, Qiao ; Hong-gui, Han

  • Author_Institution
    Coll. of Electron. & Control Eng., Beijing Univ. of Technol., Beijing
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    525
  • Lastpage
    530
  • Abstract
    A new neural fuzzy algorithm based on the method of growing self-organizing network is proposed in this paper. Then the fuzzy rules can be changed on-line, it takes the experience out of the necessary side for the number of the fuzzy rules. A novel learning algorithm based on dynamic descent gradient is also presented. The main salient characters of the algorithm in this paper are: 1) a new method resolves the problem of the conventional neural network which canpsilat change the structure of the network; 2) the neurons of the neural network can be changed on-line; 3) a new method for the fast learning speed can be own. This new algorithm can be used to control the dissolved oxygenic in the wastewater treatment process. The results of the experiments prove the superiority of this algorithm compared with the conventional neural fuzzy algorithm.
  • Keywords
    environmental science computing; fuzzy neural nets; learning (artificial intelligence); self-organising feature maps; wastewater treatment; fuzzy rules; growing self-organizing network; neural fuzzy algorithm; novel learning algorithm; wastewater treatment; Fuzzy systems; Wastewater treatment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-1818-3
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2008.4630418
  • Filename
    4630418