PM 2.5 concentration value prediction method based on hybrid neural network

Abstract

The invention provides a PM 2.5 concentration value prediction method based on a hybrid neural network. The method comprises the following steps: 1) acquisition of four types of sample data, the four types of sample data comprising PM 2.5 concentration historical data, PM 2.5 concentration value related index historical data, weather historical data and PM 2.5 composition analysis data; 2) collecting an initially-forecasted PM 2.5 concentration value of a first neural network; 3) collecting a secondary-prediction PM 2.5 concentration value of a second neural network; and 4) collecting a final-prediction PM 2.5 concentration value of a third neural network, and outputting the final PM 2.5 concentration predication value. Besides the three kinds of data of PM 2.5 concentration value historical data, the PM 2.5 concentration value related index historical data and the weather historical data, the PM 2.5 composition analysis data is also introduced, so that PM 2.5 concentration value change and development rules can be accurately described and prediction accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of prediction of air particulate matter PM2.5 concentration value, in particular to a prediction method of PM2.5 concentration value based on a hybrid neural network. Background technique [0002] Air pollution has become the focus of attention these days. In densely populated cities, air pollution has seriously affected people's health and life. Among the air pollution indicators, the concentration of PM2.5 (particulate matter with a diameter less than or equal to 2.5 microns) has become a symbolic detection indicator for measuring air quality. The prediction of PM2.5 concentration in the future time period based on historical data has become a research problem with strong academic significance and application value. [0003] In order to solve the above problems, Shi Xuhua and others used the patent "A Method for Predicting PM2.5 Concentration in Regional Air" to predict the concentration value of PM2.5 b...

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Problems solved by technology

[0005] In order to overcome the shortcomings that the existing PM2.5 concentration value prediction method cannot describe the change and development law of PM2.5 concentration value and the prediction accuracy is low, the present invention adopts the historical data of PM2.5 concentration value and the history of related indicators of PM2.5 concentration value In addition to the three types of data, data and meteorological historical data, PM2.5 composition analysis data is also introduced to provide a PM2.5 based on hybrid neural network that accurately describes the change and development of PM2.5 concentration values ​​and improves prediction accuracy. Concentration Value Prediction Method

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