基于模糊聚类的海水水质监测技术研究  

Research on the seawater quality monitoring technology based on the fuzzy clustering

作　　者：陈嵩[1] 张钢[2] 

机构地区：[1]国家海洋局天津海水淡化与综合利用研究所,天津300192 [2]天津大学计算机科学与技术学院,天津300072

出　　处：《海洋通报》2013年第5期535-539,共5页Marine Science Bulletin

摘　　要：海水水质监测数据纷繁复杂,为了在海量的数据中提取有效数据进行分析,采用模糊聚类实现对监测数据的分析处理。对监测数据分析结构做了简要说明,接着分析模糊聚类C聚类均值算法(FCM)不足之处,提出了基于不完整数据样本的FCM算法,最后采用海水赤潮数据不完整样本进行实例仿真,实验证明,该算法在处理不完整样本数据时有一定的优势。Due to the complicated seawater quality monitoring data, in order to extract the effective data from vast amounts of data, this article used the fuzzy clustering to analyze the monitoring data processing. This study made a brief analysis of monitoring data structure, then analyzed the fuzzy C mean clustering algorithm （FCM）, and based on incomplete data samples,it proposed the FCM algorithm,and finally used incomplete sample of the red tide data to carry out the instance simulation. The experiment results showed that in dealing with incomplete data samples,the algorithm had some advantages,and it was worthy of research.

关 键 词：海水水质监测 模糊聚类 模糊C均值聚类算法 不完整数据样本FCM 

分 类 号：P76[天文地球—海洋科学]