Abnormal Data Detection Algorithm for Dam Safety Monitoring Based on DBSCAN
To effectively identify the abnormal values in the safety monitoring,an abnormal data detection algorithm of dam safety monitoring based on DBSCAN clustering algorithm was proposed considering the influence of environmental factors on the observed values.The residual sequence was obtained by introducing the mathematical regression model.And then the residual sequence was analyzed by using the DBSCAN algorithm.The anomaly detection test was carried out on the common periodic,trend and irregular data in dam safety monitoring.The experimental results show that the preci-sion,recall and accuracy of the algorithm are above 0.99 for all kinds of abnormal addition modes,which has better appli-cability and robustness than the traditional methods.
NETL
NSTL
万方数据
维普
