A PM2.5 concentration prediction method based on multivariate statistical analysis and LSTM fusion

Abstract

The invention relates to the field of artificial intelligence and big data, in particular to a PM2.5 concentration prediction method based on multivariate statistical analysis and LSTM fusion, which comprises the following steps: analyzing the advantages and disadvantages of the two on the theoretical level, and constructing a fusion algorithm based on the two on the basis; acquiring meteorological data and pollutant data from a provincial control point and a national control point; Sampling data in recent half a year, and analyzing the correlation between each factor and the PM2.5 concentration by using a Pearson correlation coefficient; Dividing all the data into three parts, namely training data, test data and prediction data, training a model by using the training data, and setting related model parameters; Inputting test data into the model; According to the method, by analyzing the time and space characteristics of PM2.5, the data is subjected to dimensionality reduction, the deep data characteristics of PM2.5 are mined through the deep learning technology, the data operation speed is greatly increased, prediction work can be carried out in real time by combining with improvement of precision, and the problem of data lagging is solved.

Description

technical field [0001] The invention relates to the fields of artificial intelligence and big data, in particular to a PM2.5 concentration prediction method based on multivariate statistical analysis and LSTM fusion. Background technique [0002] With the improvement of people's living standards, the ratio of urbanization, industrialization, and population urbanization, that is, the ratio of the three modernizations, continues to increase. However, the over-exploitation of resources and over-consumption of energy have broken the original ecological balance system, and environmental issues have been paid more and more attention by governments of all countries. Especially in recent years, smog weather has frequently appeared, and the problem of PM2.5 pollution is extremely serious. In order to reasonably predict the concentration of PM2.5, experts from various countries have proposed various methods. The prediction methods can be divided into two categories according to the ...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention solves the problem of too long convergence time and overfitting in the traditional method, and proposes a PM2.5 concentration prediction method based on multivariate statistical analysis and LSTM fusion

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