Precipitation prediction method and system

Abstract

The invention discloses a precipitation prediction method and system. The method comprises the steps of collecting historical precipitation data; processing the historical precipitation data to obtainprocessed precipitation data; decomposing the processed precipitation data by adopting an MEEMD method to obtain a plurality of decomposition items and remainder items with different frequencies; determining a precipitation prediction model; wherein the precipitation prediction model comprises a trained convolutional neural network, an optimized support vector machine and an optimized BP neural network; and predicting the precipitation through the precipitation prediction model according to the decomposition items and the remainder items. According to the method, the MEEMD is utilized to decompose the precipitation data into different decomposition items, the convolutional neural network, the particle swarm optimization support vector machine and the BP neural network optimized by the artificial ant colony algorithm are adopted to establish the combined prediction model for the different decomposition items, prediction errors caused by data non-smoothness are reduced, and the prediction precision is improved.

Description

technical field [0001] The invention relates to the field of precipitation forecasting, in particular to a precipitation forecasting method and system. Background technique [0002] Because precipitation is affected by many physical elements such as atmospheric circulation, hydrometeorological elements, and physical geography, it is a weakly correlated, highly complex nonlinear dynamic system, and its interannual variation does not move in a fixed cycle. Instead, it contains changes and local fluctuations on various time scales. This characteristic makes medium and long-term precipitation forecasting more difficult and less accurate. Contents of the invention [0003] The purpose of the present invention is to provide a precipitation forecasting method and system for fast and accurate forecasting of precipitation. [0004] To achieve the above object, the present invention provides the following scheme: [0005] A precipitation forecasting method, comprising: [0006] C...

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Problems solved by technology

[0002] Because precipitation is affected by many physical elements such as atmospheric circulation, hydrometeorological elements, and physical geography, it is a weakly correlated, highly complex nonlinear dynamic system, and its interannual variation does not move in a fixed cycle. Instead, it contains changes and local fluctuations on various time scales. This characteristic makes it difficult and less accurate to predict precipitation in the medium and long term.

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