空气质量指数预测方法综述

A review of air quality index prediction methods

随着人们对美好生活需求的日益增长,空气污染成为社会发展过程中的焦点问题。由于影响空气质量的因素有很多,例如污染物浓度、地理位置、人类行为等因素,因而使空气质量预测结果的精确性无法保证。精准的空气质量指数预测可以为大气污染防治提供参考依据,从而做出有效的决策。本文以综述的方式对近年来空气质量指数预测方法进行分析与总结,分别介绍了当前空气质量指数预测的三种主要方法:统计预测、机器学习预测以及组合预测方法,最后讨论了当前空气质量指数预测中存在的一些挑战和未来的研究方向,以期为相关研究提供参考。

With the growing demand for a better life,air pollution has become a focal point in the process of social development.Many factors affect air quality,such as pollutant concentrations,geographic location,human behavior,and other factors,so it is not easy to guarantee the accuracy of air quality prediction results.Accurate AQI forecasts can provide a reference basis for air pollution control and prevention so that effective decisions can be made.This paper analyzes and summarizes the air quality index prediction methods in recent years in an overview manner.Three main current approaches to AQI prediction are presented:statistical prediction,machine learning prediction,and combined prediction methods,respectively.Finally,some of the current challenges and future research directions in AQI prediction are discussed to provide references for related research.