城市空气粉尘污染空间集聚数据智能挖掘技术研究
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摘要
数据挖掘技术对城市空气粉尘污染空间集聚情况分析的越准确,粉尘污染治理工作进行的就越顺利,然而目前存在的数据挖掘技术却恰恰存在分析准确不足的问题。提出一种新的城市空气粉尘污染空间集聚数据智能挖掘技术。该技术主要分为四部分:首先按照城市空间结构进行粉尘污染数据采集,之后对数据进行预处理,包括数据清理,数据集成,数据变换,数据归约等,然后构建基于模糊评判的数据挖掘模型,最后利用模型实现城市空气粉尘污染空间集聚数据智能挖掘。
The more accurate the data mining technology is in analyzing the spatial agglomeration of urban air dust pollution, the smoother the dust pollution control work will be. The existing data mining technology has the problem of inaccurate analysis. Aiming at the above problems, a new intelligent data mining technology for spatial agglomeration of urban air dust pollution is proposed. The technology is mainly divided into four parts:firstly, dust pollution data is collected according to the urban spatial structure, and then the data is pretreated, including data cleaning, data integration, data transformation, data reduction, etc. Then, a data-mining model based on fuzzy evaluation is constructed. Finally, Finally, the model is used to realize the intelligent mining of urban air dust pollution spatial agglomeration data.
The more accurate the data mining technology is in analyzing the spatial agglomeration of urban air dust pollution, the smoother the dust pollution control work will be. The existing data mining technology has the problem of inaccurate analysis. Aiming at the above problems, a new intelligent data mining technology for spatial agglomeration of urban air dust pollution is proposed. The technology is mainly divided into four parts:firstly, dust pollution data is collected according to the urban spatial structure, and then the data is pretreated, including data cleaning, data integration, data transformation, data reduction, etc. Then, a data-mining model based on fuzzy evaluation is constructed. Finally, Finally, the model is used to realize the intelligent mining of urban air dust pollution spatial agglomeration data.
引文
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[6]董师倢.数据挖掘中的数据预处理技术[J].信息与电脑,2016(19):144-145.
[7]梅毅,熊婷,罗少彬.复杂属性环境下NoSQL分布式大数据挖掘方法研究[J].科学技术与工程,2017,17(9):239-243.
[2]刘伯华,金辉,周涛,等.廊坊市主城区粉尘铅污染调查分析[J].中国人口·资源与环境,2016(S1):106-108.
[3]申庆喜,李诚固,刘倩.基于服务设施布局视角的城市空间结构研究——以长春主城区为例[J].经济地理,2017,37(3):129-135.
[4]刘淑虎,任云英,马冬梅.“三位一体”的城市空间结构特征解析体系研究——以计划经济时期西安城市空间为例[J].华中建筑,2016(4):82-87.
[5]党红恩,赵尔平,孙海霞.云计算下非显著性特征数据实时挖掘方法仿真[J].计算机仿真,2017,34(7):203-206;330.
[6]董师倢.数据挖掘中的数据预处理技术[J].信息与电脑,2016(19):144-145.
[7]梅毅,熊婷,罗少彬.复杂属性环境下NoSQL分布式大数据挖掘方法研究[J].科学技术与工程,2017,17(9):239-243.