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
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;
Conference_Titel :
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4673-0458-0
DOI :
10.1109/CDCIEM.2012.141
