集美大学学报（自然科学版）2024，Vol.29Issue(1)：24-31,8.DOI:10.19715/j.jmuzr.2023.04.04
基于参数自适应DBSCAN算法的浮标位置数据异常检测
Buoy Position Data Abnormaly Detection Based on Parameter Adaptive DBSCAN Algorithm
摘要
Abstract
In the process of using the telemetry and remote-control system to collect data,it is easy to be disturbed by external factors and generate abnormal location data.To address this problem,a K-nearest neigh-bor optimized parameter adaptive DBSCAN algorithm is proposed to detect the anomalies in buoy position data.The algorithm proposed generates a list of optimal distance values ε in adjacent waters and the number of sam-ple points MinPts through the analysis of the distribution characteristics of the dataset,and the introduction of the Calinsky-Harabas index to score the parameters in the list,and the parameter corresponding to the highest score is used as the optimal parameter to realize the adaptive clustering of DBSCAN algorithm.The experimen-tal results show that the proposed algorithm can adaptively select the optimal parameters and realize the detec-tion of abnormal buoy telemetry position data.关键词
浮标位置/异常检测/遥测遥控系统/DBSCAN算法/K近邻算法/CH指数Key words
buoy position/abnormal detection/telemetry and remote control system/DBSCAN algorithm/K-nearest neighbor algorithm/CH index分类
交通工程引用本文复制引用
章新亮,肖虹,周世波..基于参数自适应DBSCAN算法的浮标位置数据异常检测[J].集美大学学报（自然科学版）,2024,29(1):24-31,8.基金项目
福建省自然科学基金项目(2020J01658) （2020J01658）
船舶辅助导航技术国家地方联合工程研究中心开放课题(HHXY2020002) （HHXY2020002）
集美大学博士启动基金项目(ZQ2019012) （ZQ2019012）
