计算机科学 ›› 2019, Vol. 46 ›› Issue (7): 211-216.doi: 10.11896/j.issn.1002-137X.2019.07.032
蒋华,武尧,王鑫,王慧娇
JIANG Hua,WU Yao,WANG Xin,WANG Hui-jiao
摘要： 针对海洋Argo浮标监测数据中的异常数据挖掘问题,在改进K均值算法的基础上,提出基于距离为准则进行海洋异常数据判定的异常检测算法。该算法重新定义海洋数据邻近度,并根据数据的规模以及分布情况,区块化、自适应地筛选备选初始聚类中心;在算法迭代过程中,运用簇内,数据对象相对于聚类中心的距离均值,全局考量类簇内,符合异常特征的数据对象进行异常检测。通过仿真数据集和真实数据集分别进行实验验证,对比结果表明:该算法在聚类性能以及异常检测方面都优于对比算法。
中图分类号:
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