Method for predicting AQI

Abstract

The present invention provides a method for predicting AQI (Air Quality Index), comprising the following steps: obtaining historical weather data of a predicted area, wherein the historical weather data comprises historical AQI values, and historical meteorological data; preprocessing the historical weather data, wherein the preprocessing comprises checking compliance, converting the historical weather data into data suitable for computer processing, and generating derived fields; building a plurality of AQI prediction models based on a feature selection model, a regression analysis model, and a time series analysis model; evaluating the built AQI prediction models, and selecting the AQI prediction model with the highest prediction accuracy to serve as the optimal AQI prediction model; deploying the optimal AQI prediction model to the predicted area; and displaying AQI relevant indexes of the predicted area. The method does not need a mass of data and hardware equipment with high configuration, is simple and scientific, and can accurately predict the AQI of the specific area.

Description

technical field [0001] The invention relates to a method for predicting an air quality index, which belongs to the technical field of environmental detection. Background technique [0002] With the development of society and the progress of economy, environmental problems are becoming more and more serious, especially in recent years, serious air pollution directly endangers people's health, and the development of environmental detection and treatment technology has been widely valued and supported. Air Quality Index (AirQualityIndex, AQI) is a dimensionless index that quantitatively describes the state of air quality, predicts more accurate future air quality, can provide guidance for environmental testing research, and provide convenience for people to arrange travel. [0003] The existing air quality index prediction methods mainly include: [0004] The SPRINTARS (Spectral Radiation-Transport Model for Aerosol Species) method is a numerical model developed to simulate th...

AI Technical Summary

Problems solved by technology

Based on the air-sea coupling model MIROC, the main atmospheric aerosols that exist naturally and artificially in the troposphere, including black carbon, organic matter, sulfate, soil particles and sea salt particles, are studied. This method is scientific to a certain extent. However, there are the following disadvantages: On the one hand, this method mainly considers the overall factors of atmospheric circulation from a macro perspective, and analyzes the diffusion form of pollutants from the dimension of atmospheric circulation, and it is difficult to distinguish in detail the specific climate conditions of specific regions (such as cities)

Because the specific climate conditions in the same area will change due to seasons, time periods, and even human factors. For example, the discharge and accumulation of pollutants are obviously different before and after a new chemical plant in a certain area. On the other hand, this method has a huge amount of data collection and calculation, at least it needs to collect a large amount of specific information on pollution sources and satellite meteorological information, and at the same time configure high-performance hardware equipment to provide data processing functions, which is costly and professional. , not suitable for ordinary users

[0005] The second is the WRF (Weather Research and Forecasting Model)-Chem (Chemistry) method based on the calculation of the chemical forecast model. This method also requires extremely high computing resources and is difficult to implement.

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