• DocumentCode
    3759429
  • Title

    A Modified K-Means Algorithm Based RBF Neural Network and Its Application in Time Series Modelling

  • Author

    Yiping Jiao;Yu Shen;Shumin Fei

  • Author_Institution
    Sch. of Autom., Southeast Univ., Nanjing, China
  • fYear
    2015
  • Firstpage
    481
  • Lastpage
    484
  • Abstract
    In this paper, a modified K-means based RBFNN is discussed. To improve the performance of RBFNN, an initial cluster centers (ICCs) selection strategy is proposed for K-means algorithm. The algorithm takes breadth preferred subset of samples as ICCs to cover the sample space using greedy strategy. The results shows that the proposed algorithm can improve the performance of RBFNN remarkably in chaotic time series modelling.
  • Keywords
    "Clustering algorithms","Time series analysis","Machine learning algorithms","Partitioning algorithms","Training","Neural networks","Algorithm design and analysis"
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing and Applications for Business Engineering and Science (DCABES), 2015 14th International Symposium on
  • Type

    conf

  • DOI
    10.1109/DCABES.2015.126
  • Filename
    7429660
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3759429