Application of the Coupling Time Series Model Based onWavelet and Runs in Precipitation Forecast

doi:10.3969/j.issn.1001-5485.2014.08.0042014,31(08):18-22,28

Journal of Changjiang River Scientific Research Institute ›› 2014, Vol. 31 ›› Issue (8): 18-22.DOI: 10.3969/j.issn.1001-5485.2014.08.0042014,31(08):18-22,28

• RIVER-LAKE SEDIMENTATION AND REGULATION • Previous Articles Next Articles

Application of the Coupling Time Series Model Based onWavelet and Runs in Precipitation Forecast

PENG Gao-hui¹, WEI Bao-lei¹, MA Jian-qin²

1.School of Mathematics and Information Science, North China University of Water Resources andElectric Power, Zhengzhou 450045, China;
2.School of Water Conservancy, North China University ofWater Resources and Electric Power, Zhengzhou 450045, China

Received:2014-08-12 Revised:2014-08-12 Published:2014-08-01 Online:2014-08-01

Abstract

Abstract: According to the multi-scale and non-stationary features of precipitation time series, we choose db3 wavelet and use Mallat algorithm to decompose the precipitation series in two types of scales to solve the problem of long-time forecast with inadequate precision. After independent Runs tests between the decomposing consequences, we established the coupling ARIMA models based on Wavelet and Runs to forecast precipitation in the city of Zhengzhou from 2008 to 2012. It is proved that the accuracy of the coupling model is higher than that of traditional model. We predict the precipitation per month from 2013 to 2015 in order to provide a basis for decision-making. This research is of theoretical significance and application value.

Key words: precipitation forecast, Wavelet transform, Runs, coupling model, ARIMA

CLC Number:

TV211.1

PENG Gao-hui, WEI Bao-lei, MA Jian-qin. Application of the Coupling Time Series Model Based onWavelet and Runs in Precipitation Forecast[J]. Journal of Changjiang River Scientific Research Institute, 2014, 31(8): 18-22.

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Application of the Coupling Time Series Model Based onWavelet and Runs in Precipitation Forecast

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