• DocumentCode
    2713052
  • Title

    Back Propogation(BP)-neural network for tropical cyclone track forecast

  • Author

    Wang, Yuanfei ; Zhang, Wei ; Fu, Wen

  • Author_Institution
    Key Lab. of Geographic Inf. Sci., East China Normal Univ., Shanghai, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Tropical Cyclone (TC) track prediction is still a big and unsolved problem from the perspectives of theory and application due to the complicated and non-linear physical mechanisms and lack of calculating capabilities and observations. Neural Network works effectively and efficiently in simulating non-linear relationships. Therefore, the present study employs the BP-neural network to predict TC tracks. After the model is trained by historical TC track data (e.g., latitude and longitude), it perform relatively well in tropical cyclone prediction according to the verification.
  • Keywords
    atmospheric movements; atmospheric techniques; neural nets; storms; weather forecasting; back propagation neural network; nonlinear physical mechanisms; tropical cyclone prediction; tropical cyclone track forecast; Artificial neural networks; Neurons; Prediction algorithms; Predictive models; Tracking; Training; Tropical cyclones; BP; forecasting; tropical cylone;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5981095
  • Filename
    5981095