Application of Fuzzy Neural Network to the Flood Season Precipitation Forecast

Author

Wu, Hui ; Lin, Xi

Author_Institution

Hainan Inst. of Meteorol. Sci., Haikou, China

Volume

2

fYear

2009

fDate

24-26 April 2009

Firstpage

39

Lastpage

43

Abstract

Taking the flood season (from May to October) precipitation in Hainan province as the forecast object, the application of fuzzy neural networks forecasting method with different forecast factors is studied. The results show that the new model based on principal component analysis is significantly superior to the traditional stepwise regression model and other fuzzy neural networks models which select other factors in prediction accuracy and prediction stability. It can be applied to operational short-term climate forecast.

Keywords

atmospheric precipitation; climatology; floods; fuzzy logic; fuzzy neural nets; geophysics computing; principal component analysis; weather forecasting; China; Hainan province; climate forecasting; flood; fuzzy logic; fuzzy neural network; precipitation forecasting; principal component analysis; traditional stepwise regression model; Computer networks; Floods; Fuzzy logic; Fuzzy neural networks; Meteorology; Neural networks; Ocean temperature; Predictive models; Sea level; Weather forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on

Conference_Location

Sanya, Hainan

Print_ISBN

978-0-7695-3605-7

Type

conf

DOI

10.1109/CSO.2009.73

Filename

5193893