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
Link To Document