学术论文

      基于模糊C均值聚类算法的海洋环境监测研究

      Research on marine environment monitoring based on fuzzy C-means clustering algorithm

      摘要:
      该文将模糊C均值聚类算法(FCM)应用到海洋环境监测数据的挖掘中.应用数据预处理算法,对莱州湾海域的历史海洋数据包括pH值、温度、溶解氧浓度等进行处理;应用FCM算法对不同海域的数据进行聚类,以此获得相近海域的数据特征;将该算法应用到海水污染预警中,用于区分污染和未污染海水样本.实测结果表明了算法的有效性,为海水污染预警提供了一种新的思路.
      Abstract:
      In this paper, the fuzzy C-means clustering algorithm( FCM) is applied to the mining of marine environmental monitoring data. The data of the sea area of Laizhou Bay, including pH value, temperature,dissolved oxygen concentration, and so on, are analyzed by data preprocessing algorithm. FCM algorithm is used to cluster the data of different sea areas, so as to obtain the data characteristics of similar sea area. The algorithm is applied to the prediction of seawater pollution,which is used to distin-guish between the polluted and non-polluted seawater samples. The results show that the algorithm is ef-fective and provides a new way for the early warning of sea water pollution.
      作者: 张彦军 张姗姗
      Author: ZHANG Yanjun ZHANG Shanshan
      作者单位: 青岛科技大学 自动化与电子工程学院,山东 青岛,266042
      年,卷(期): 2017, (6)
      分类号: TP391.41
      在线出版日期: 2018年1月4日
      基金项目: 山东省自然科学基金,青岛科技大学博士科研基金