摘要
为了识别污水处理数据中的异常数据,应用了一种基于最近邻聚类和遗传优化算法的异常检测算法。算法采用基于距离的异常因子来度量异常数据的异常程度。通过分析异常类别的数据,建立故障诊断的规则。实验结果表明,该方法能够有效地检测中污水处理数据中的异常数据。
In order to identify the abnormal data from wastewater treatment history dataset,an abnormity detection algorithm based on the nearest neighbor clustering and genetic optimization algorithm is practiced.The algorithm applies distance-based outlier factor to measure the abnormity degree of an outlier.By analyzing the abnormal data,a fault diagnosis rule is established.Experimental results show that the method can effectively detect abnormal data in wastewater treatment history dataset.
出处
《计算机应用与软件》
CSCD
2011年第6期199-201,共3页
Computer Applications and Software
关键词
最近邻聚类
遗传算法
异常因子
故障规则
污水处理
Nearest neighbor clustering Genetic algorithm Outlier factor Fault rule Wastewater treatment
