基于数据挖掘的城市空气污染物扩散时空特征研究

Analysis on Spatial and Temporal Characteristics of Urban Air Pollutant Diffusion Based on Data Mining

为提升城市空气污染物扩散时空特征分析效果,提出一种基于数据挖掘的城市空气污染物扩散时空特征分析方法。从影响空气污染物扩散的因素入手,模拟区域气温分布空间和风场,建立空气污染物扩散方程,在获得初始数据后,利用数据挖掘技术对数据聚类处理,统一数据量纲,得到关联性强的数据集合,利用处理后的数据,计算出空气污染物的季节指数,经过多次细化计算,得到污染物的月趋势和日趋势分析结果。实验结果表明:面对大气稳定程度的改变,提出的污染物扩散时空特征分析方法分析误差小,成分相关性强,整体空间适应性得到了增强。

In order to improve the analysis effect of spatio-temporal characteristics of urban air pollutant diffusion,a method of spatio-temporal characteristics analysis of urban air pollutant diffusion based on data mining is proposed.From the perspective of the influence factors of air pollutant diffusion,the temperature distribution of space and wind field was chosen as simulation area to set up air pollutant diffusion equation.After the initial data,the study uses data mining techniques to cluster data processing,unified data dimension to get strong correlation data collection.The study uses the processed data to calculate the season of air pollutant index,after a detailed calculation for many times.The analysis results of monthly trend and daily trend of pollutants were obtained.The experimental results show that,in the face of the change of atmospheric stability,the proposed method for analyzing the spatial and temporal characteristics of pollutant diffusion has small analysis error,strong component correlation,and the overall spatial adaptability is enhanced.