基于大数据技术的雾霾天气预测模型研究

Research on Haze Weather Prediction Model Based on Big Data Technology

雾霾天气成因复杂,预测较为困难。经深入分析相关技术和文献资料,在大数据技术支持下,将时空维度中已知空气质量数据与气象数据动态集成,构建了一种基于深度神经网络技术在时间维度和空间维度相融合的空气质量预测模型——基于深度神经网络的空气质量预测模型。经实验证实,此模型可预测目标站点未来的空气质量状况,且预测结果更加准确,可为环境治理提供理论参考。

The causes of haze weather are complex and difficult to predict.Through in-depth analyses of relevant technologies and literature,under the support of big data technology,the known air quality data in the space-time dimension and meteorological data are dynamically integrated.An air quality prediction mod⁃el based on the deep neural network technology,which combines the time dimension and the space dimen⁃sion,is constructed.The experimental results show that the model can predict the future air quality of the tar⁃get station,and the prediction results are more accurate,which can provide a theoretical reference for envi⁃ronmental governance.