DocumentCode
1679110
Title
Research on Precipitation Prediction Based on Time Series Model
Author
Qing, Chang ; Xiaoli, Zhao ; Kun, Zhang
Author_Institution
Coll. of Comput. & Eng., Xinxiang Univ., Xinxiang, China
fYear
2012
Firstpage
568
Lastpage
571
Abstract
It should improve the forecasting accuracy in the study of precipitation prediction. It is difficultly to predict climate because of the dynamic characteristics of sample set as well as the effect of environmental factors. In order to improve the accuracy, a novel model based on time series and environmental factors was introduced in this paper. Firstly, the environmental factors were nonlinear screened by support vector machine (SVM). Secondly, estimated the order by controlled autoregressive (CAR). Lastly, reliability of SVM-CAR was validated by one-step prediction method. The simulation result of drought forecasting showed that this method has the advantages of high-precision and has a good prospect in drought and flood forecasting.
Keywords
atmospheric precipitation; autoregressive processes; floods; geophysics computing; support vector machines; time series; controlled autoregressive; drought forecasting; environmental factor; flood forecasting; one-step prediction method; precipitation prediction; support vector machine; time series model; Accuracy; Analytical models; Data models; Environmental factors; Predictive models; Support vector machines; Time series analysis; Multiple regressions; Precipitation prediction; SVM; Time series model;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location
Hunan
Print_ISBN
978-1-4673-0458-0
Type
conf
DOI
10.1109/CDCIEM.2012.141
Filename
6178539
Link To Document