计算机与数字工程2025，Vol.53Issue(2)：332-337,346,7.DOI:10.3969/j.issn.1672-9722.2025.02.007
基于神经网络与深度学习的PM2.5预测模型研究
Research on PM2.5 Prediction Model Based on Neural Network and Deep Learning
摘要
Abstract
The problem of atmospheric pollution is becoming more and more serious,and the hazy weather with PM2.5 as the main factor has seriously affected the life of residents.Accurate and efficient PM2.5 concentration prediction is important for environ-mental pollution management.Neural networks and deep learning,as a popular research technology in the direction of artificial intel-ligence in recent years,have become indispensable tools in the field of environmental engineering because of their powerful data analysis,nonlinear fitting and feature extraction capabilities.This paper introduces five common methods of neural networks and deep learning in PM2.5 prediction,which are BP neural network,recurrent neural network,convolutional neural network,radial basis neural network,and feedback neural network,analyzes the advantages and disadvantages of the five models,describes the prediction of PM2.5,and finally outlooks the future development direction of deep learning in the field of PM2.5 prediction.关键词
神经网络/深度学习/BP神经网络/循环神经网络/卷积神经网络Key words
neural network/deep learning/BP neural network/recurrent neural network/convolutional neural network分类
数理科学引用本文复制引用
任瑛,王思源,夏必胜..基于神经网络与深度学习的PM2.5预测模型研究[J].计算机与数字工程,2025,53(2):332-337,346,7.基金项目
国家自然科学基金项目(编号:61866038,61763046,62041212) （编号:61866038,61763046,62041212）
陕西省自然科学基础研究计划项目(编号:2021JM-418) （编号:2021JM-418）
延安大学博士科研启动项目(编号:YDBK2019-06) （编号:YDBK2019-06）
延安市科技专项资助项目(编号:2019-01,2019-13) （编号:2019-01,2019-13）
延安大学疫情防控应急科研项目(编号:YDFK073) （编号:YDFK073）
延安市科技局项目(编号:203010096) （编号:203010096）
延安大学校级项目(编号:205040306)资助. （编号:205040306）
