井冈山大学学报（自然科学版）Issue(6)：48-53,6.DOI:10.3969/j.issn.1674-8085.2014.06.011
基于改进凝聚层次聚类算法的生态环境监测采样点优选技术研究
RESEARCH ON SELECTION OF PREFERRED ECOLOGICAL ENVIRONMENT MONITORING SAMPLING POINT BASED ON AN IMPROVED HIERARCHICAL AGGLOMERATIVE CLUSTERING ALGORITHM
摘要
Abstract
With the rapid development of economy in our country, ecological environment is becoming more and more stressful. Environmental monitoring and early warning on the environment are important aspects to maintain the ecological green and sustainable development. In order to get the most optimal ecological environment data under limited conditions, we should carry out a reasonable selection of a preferred sampling point. Therefore, the selection of a preferred environmental monitoring sampling point is an important part of ecological environmental monitoring. Initial environment monitored data is processed first by using a series of data preprocessing techniques. Therefore, environment monitored data is clustered by using a clustering algorithm based on improved agglomerative hierarchy. Finally, a sampling point closest to the cluster center is selected as a preferred sampling point. The whole process is simple and effective and has a realistic significance for selecting a preferred sampling point during a small and medium scale ecological environment monitoring.关键词
环境监测/采样点/数据聚类/凝聚层次聚类Key words
environmental monitoring/sampling point/data clustering/hierarchical agglomerative clustering分类
资源环境引用本文复制引用
彭硕,郭晨,周松,王博..基于改进凝聚层次聚类算法的生态环境监测采样点优选技术研究[J].井冈山大学学报（自然科学版）,2014,(6):48-53,6.基金项目
国家科技支撑计划项目(2012BAC11B03)；江西省科技支撑计划项目(20123BBG70221) （2012BAC11B03）
