地区差异城市群大气污染多维度数据采集仿真

Multi-Dimensional Data Collection of Air Pollution in Regionally Different City Groups

针对目前城市大气污染数据采集过程存在误差较大问题,采用决策树组织组建新的地区差异城市群大气污染多维度数据采集模型。在城市群大数据支持下,组建与气象信息相关的决策树组织。采用定点采集监测数据方法实现地区差异城市群大气污染多维度数据分析。结合多维度采集数据库,分别计算不同污染气体的实际排放量,构建大气污染多维度数据采集模型。为验证所提方法的有效性,设计一次仿真。由实验结果可知,所设计模型能够降低数据整合时间,且成本更低,模型采集的大气污染数据具有更高的准确性。得出结论,研究构建的模型具有可靠应用有效性。

This paper proposes a new multi-dimensional data acquisition model of air pollution in urban groups with regional differences through the utilization of decision tree organization for reducing the error of urban air pollution data collection.The decision tree organization related to meteorological information was founded with the support of big data of urban groups.The method of fixed-point collection and monitoring data was adopted to complete multi-dimensional data analysis of air pollution in different urban groups.According to the multi-dimensional collection database,the actual emissions of different pollutants were calculated,and the multi-dimensional data acquisition model about air pollution was established.A simulation experiment was designed for verifying the effectiveness of the model.The results show that the model designed in this paper has low data integration time,low cost,high data acquisition accuracy and excellent application effectiveness.