• DocumentCode
    3332650
  • Title

    Analysis on Evolution of Hengsha Passage in the Yangtze River Estuary with BP Artificial Neural Network

  • Author

    Gu Jie ; Qin Xin ; Li Wenting ; Chen Wei ; Ma Danqing

  • Author_Institution
    Coll. of Marine Sci., Shanghai Ocean Univ., Shanghai, China
  • fYear
    2011
  • fDate
    10-12 May 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, based on the analysis of hydrology and sediment data, a BP artificial neural network model which has been applied maturely and widely is established to study the relationship between the middle-section width of the Hengsha Passage and the three other factors the runoff, the sediment discharge of the South Branch and the split ebb flow ratio of the North Channel. With a structure on 3-1-7-1 and appropriate parameters, the BP artificial neural network is well trained and tested. The model can perform well to predict the evolution of the Hengsha Passage. The proper regulation in the Hengsha Passage, which may benefit to the operation of the deep water channel in North Passage, is suggested.
  • Keywords
    data analysis; hydrology; neural nets; rivers; sediments; BP artificial neural network model; China; Hengsha passage evolution; Yangtze River estuary; deep water channel; hydrology analysis; north channel; runoff process; sediment data analysis; sediment discharge; split ebb flow ratio; Artificial neural networks; Discharges; Floods; History; Predictive models; Rivers; Sediments;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2151-7614
  • Print_ISBN
    978-1-4244-5088-6
  • Type

    conf

  • DOI
    10.1109/icbbe.2011.5780808
  • Filename
    5780808