基于自组织神经网络的生态环境污染信息监测研究  

Information Monitoring of Ecological Environment Pollution Based on Self-organizing Neural Network

作　　者：尹波 Yin Bo(Xiangdu District Branch of Xingtai Ecological Environment Bureau,Xingtai 054001,China)

机构地区：[1]邢台市生态环境局襄都区分局,河北邢台054001

出　　处：《环境科学与管理》2022年第11期144-148,共5页Environmental Science and Management

摘　　要：由于生态环境监测数量巨大,污染物种类繁多,监测十分困难。为此,提出基于自组织神经网络的生态环境污染信息监测研究。在监测区域内对土壤进行剖面采样,选择并制定对应的生态污染监测指标,直接检测有机污染物土壤样本。采用自组织神经网络模型对生态环境污染区域的污染情况进行空间聚类分析,构建土地生态污染监测信息模型,实现土地生态环境污染信息监测。实验证明,所提方法能够从多维度对场地的污染状况进行监测,提取内部关键信息,在监测过程中,能够根据聚类特征分析空间分布特征,实现优化筛选,减少监测项目,降低工作成本。Ecological motioning is difficult due to the huge amount of ecological data and the wide variety of pollutants.This paper studies the ecological environment pollution information monitoring based on self-organizing neural network.It proposed the profile sampling of soil in the monitoring area,selection and development of corresponding ecological pollution monitoring indicators,and direct detection of organic pollutant soil samples.The self-organizing neural network model is used to carry out spatial clustering analysis of the pollution situation of the ecological environment pollution area,and the land ecological pollution monitoring information model is constructed to realize the land ecological environment pollution information monitoring.Experiments show that the proposed method can monitor the pollution status of the site from multiple dimensions and extract the internal key information.In the monitoring process,it can analyze the spatial distribution characteristics according to the clustering characteristics,achieve optimization screening,reduce monitoring items and reduce work costs.

关 键 词：生态环境污染 污染监测 信息监测 自组织神经网络 

分 类 号：X92[环境科学与工程—安全科学]