Middle-and-long-term rainfall forecast modeling method for whole-process coupling machine learning

Abstract

The invention discloses a medium-and-long-term rainfall forecast modeling method based on whole-process coupling machine learning, and the method comprises the following steps: S1, data processing: collecting actually measured rainfall, 130 meteorological-climate indexes and other data, and determining a forecast structure; s2, factor screening: providing a factor screening method based on Laplacian fractional-recursive feature elimination, and obtaining a forecast factor set; s3, model construction: constructing a plurality of machine learning models, and solving a plurality of sets of sub-forecasting results by adopting the forecasting structure and the forecasting factor set; and S4, multi-model fusion: providing a multi-model fusion technology based on an improved stacking method, and outputting a final forecast result. According to the method, the latest research result of the machine learning theory is applied to each link of medium and long term rainfall forecasting, the theoretical basis is sufficient, the practical application is reasonable, and the accuracy and the reliability of month-season-year scale rainfall forecasting can be effectively improved.

Description

technical field [0001] The invention relates to the field of meteorological and hydrological forecasting, in particular to a medium- and long-term precipitation forecasting modeling method coupled with machine learning in the whole process. Background technique [0002] The medium and long-term precipitation forecast generally refers to the forecast period in the monthly-seasonal-annual scale, and gives the forecast of the total precipitation by period. As a bridge between short- and medium-term weather forecasts and climate forecasts, refined mid-to-long-term forecasts are the basic key technology to realize the scientific allocation of water resources and improve the efficiency of water resource utilization. Forecasts are instructive. At the same time, the medium- and long-term precipitation forecast is in the forecast gap in the weather-climate integrated forecast due to its complex change law and obvious forecast difficulty, and it is also the current research focus and...

AI Technical Summary

Problems solved by technology

The current research still has the following deficiencies: the medium- and long-term precipitation forecast modeling method based on machine learning is mainly divided into three links: predictor selection, forecast model construction, and multi-model result fusion. Most studies only apply machine learning to a single link , rather than a whole-process coupling study

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