基于GA-BP神经网络的供暖期空气质量指数预测分析

Prediction and analysis of air quality index in heating period based on GA-BP neural network

空气质量指数(AQI)是定量描述空气质量状况的无量纲指数,其预报工作有利于减弱或预防空气严重污染事件的发生.针对冬季供暖期AQI指数的预测问题,本文提出了一种基于遗传算法优化神经网络的预测方法.以西安市环境监测站提供的数据作为研究对象,分别建立了基于BP神经网络的AQI预测模型和基于遗传算法优化的BP神经网络AQI预测模型,并对预测结果进行了对比分析.结果表明,遗传算法优化后的神经网络(GA-BP)的预测结果在泛化能力上较BP神经网络要好,其模拟结果更接近于真实值,具有更高的精准度和精确度.

Air quality index （AQI） is anondimensional index toquantitativelydescribe the condition of air quality,the forecastwork helps toweaken or prevent the occurrence of setious air pollution incidents. According to the prediction of AQI in heating season,prediction method based on GA-BP＇s proposed in this paper. Using the monitoring data of Xi7an monitoring station as study object,a AQI prediction model based on BP neural network and a AQI prediction model based on BP neural network optimed by the genetic algorithm are established respectively, compare and analyze the predicted results of these two models. The results show that the generalization ability of GA-BP model are better than BP model,and thesimulation resutt s close to reality,has higher accuracy and precision.