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
Link To Document :
بازگشت