Computer Science ›› 2017, Vol. 44 ›› Issue (10): 222-227.doi: 10.11896/j.issn.1002-137X.2017.10.040

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Research of Multi-branch Precipitation Probability Forecasting Model

YU Lin, LV Xin, ZHOU Si-qi and LIU Xuan   

  • Online:2018-12-01 Published:2018-12-01

Abstract: The size of precipitation plays a decisive role in aspects of water dispatching decision,early warning of flood and drought control,etc.Currently,many precipitation forecasting models have already been put forward.However,due to lack of the nonlinear characteristic of precipitation process consideration,the forecasting accuracy is not high.In addition,it is difficult to use a single forecast value to effectively support the judgment,leading to the fact of lower applicability results.Aimed at the above-mentioned problems,forecasting models of year-on-year branch and month-on-month branch were constructed based on the stationarity and periodicity of precipitation,and then a multi-branch precipitation probability forecasting model (MBPPFM) was proposed.The cross selection algorithm was used in the model to well screen the forecasting results from year-on-year branch and month-on-month branch.Finally,the forecasting accuracy is improved and abnormal forecasting can be avoided.At the same time,probability and confidence values are included in the forecasting results to effectively support decision making.

Key words: Precipitation forecasting,ARMA model,BP network,Markov forecasting,Association rules,Cross model

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