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Rainfall forecast method based on kernel principal component analysis and gene expression programming

A technology of nuclear principal component analysis and expression, applied in forecasting, instruments, calculation models, etc., can solve problems such as complex law changes, reduce coupling effects, and improve the quality of precipitation forecasting

Inactive Publication Date: 2015-09-30
GUANGXI TEACHERS EDUCATION UNIV
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Problems solved by technology

[0014] The technical problem to be solved in the present invention is to overcome the deficiencies of the prior art, and according to the characteristics of many precipitation influencing factors and complex regular changes, a pre-precipitation forecasting method based on nuclear principal component analysis and gene expression programming is proposed. Combining expression programming with kernel principal component analysis and other methods to model and forecast the historical time series of precipitation-related meteorological elements to obtain higher forecast accuracy

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  • Rainfall forecast method based on kernel principal component analysis and gene expression programming
  • Rainfall forecast method based on kernel principal component analysis and gene expression programming
  • Rainfall forecast method based on kernel principal component analysis and gene expression programming

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[0036] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the specific implementation of the technical solution of the present invention will be further elaborated below in conjunction with specific diagrams, including the following steps:

[0037]Step 1: Collect the actual historical data of precipitation in the area to be forecasted and the historical data of the main meteorological elements related to precipitation in the precipitation forecast model in the same period, including geopotential height, relative humidity, specific humidity, vertical Velocity, temperature dew point difference, vorticity, divergence, vorticity advection, water vapor flux, water vapor flux divergence, potential temperature, temperature advection, sea level pressure and sea level air temperature and other elements of historical time series data, and these data cleaning;

[0038] Step 2: Calculate the correlation coeffici...

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Abstract

The invention discloses a rainfall forecast method based on kernel principal component analysis and gene expression programming. According to the rainfall forecast method, forecast factors are selected on the basis of live historical rainfall data of a governed region and collecting and cleaning of meteorological factor historical time series data in the corresponding period; the forecast factors are subjected to kernel principal component analysis; a gene expression programming rainfall forecast model is created, and live weather data of the governed area are inputted into the model to acquire a rail forecast result. By the rainfall forecast method, the problems of change rule complexity and numerous influence factors in meteorological rainfall forecast can be solved, and rainfall forecast quality can be improved effectively.

Description

technical field [0001] The invention belongs to the field of meteorological forecasting and forecasting, in particular to a precipitation forecasting method. Background technique [0002] Frequent droughts and floods have seriously affected and restricted my country's economic development. Therefore, improving the accuracy of precipitation forecasting is a very important topic in the field of meteorological forecasting. However, weather changes are affected by time and space, and the physical process of formation is very complicated, which is a very complex and changeable natural phenomenon. Atmospheric precipitation has many influencing factors, and sometimes there are dozens or even hundreds of precipitation influencing factors. For precipitation changes that show complex non-equilibrium nonlinear changes, it is difficult to predict long-term, medium-term and short-term precipitation, and it is also difficult to predict daily precipitation. predict. At present, most prec...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N3/00
Inventor 彭昱忠
Owner GUANGXI TEACHERS EDUCATION UNIV
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