Air quality index level probability prediction method and device and storage medium

Abstract

The application discloses an air quality index level probability forecasting method and device and a storage medium. The method comprises the steps: acquiring air quality data that are forecasted by multiple air quality forecasting methods and comprise air quality sub-indexes of multiple pollutants; calculating the level probability, being the probability that the air quality sub-index belongs toeach air quality sub-index level, of the air quality sub-index of each pollutant; and calculating the level probability, being the probability that the air quality index belongs to each air quality index level, of the air quality index according to the level probability of the air quality sub-index of each pollutant. According to the method, air quality prediction is carried out based on multipleprediction methods; meanwhile, the conditional probability method is adopted to give an air quality index level probability prediction result, the accuracy of the prediction result is higher, and theservice prediction requirements of related departments can be better met.

Description

technical field [0001] The present application relates to the technical field of air quality forecasting, in particular to a probabilistic forecasting method, device and storage medium of air quality index levels. Background technique [0002] In recent years, the serious problem of air pollution has attracted widespread attention. Reasonable air quality forecasts can help government departments make decisions to limit the emission of man-made pollutants, and at the same time guide the public to avoid pollution peak periods, reduce exposure time, and reduce health risks caused by pollution. The air quality model can simulate the physical and chemical reaction process of pollutants, and can give the four-dimensional spatial and temporal characteristics of pollutant concentration with physical meaning. It has become the main means of short-term near-term and medium-term air quality forecasting. [0003] The air quality model simulates the change of pollutant concentration in ...

AI Technical Summary

Problems solved by technology

At present, the probabilistic forecasting of air quality is in its infancy. Existing research mainly focuses on "diagnostic identification and analysis of key sources of uncertainty in air quality models". Construct a model quantitative uncertainty diagnosis system, and then based on numerical simulation, incorporate the various uncertainty analysis results of the model and input to form a probability forecast, and obtain the result of the probability distribution of the pollutant concentration. This method requires a large number of disturbance simulations. Computational resource requirements are high

At present, in the probabilistic forecasting research in the field of air pollution, there is no method to directly give the probabilistic forecasting of the air quality index level based on the air quality forecasting results of multiple forecasting methods, and the existing air quality probabilistic forecasting cannot meet the needs of business forecasting

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