一种快速的突变点在线检测算法设计与实现  

Design and Implementation of a Fast Online Algorithm for Mutation Point Detection

作　　者：邹俊晨 齐金鹏[1] 李娜[1] 刘佳伦 朱厚杰 ZOU Junchen;QI Jinpeng;LI Na;LIU Jialun;ZHU Houjie(School of Information Science & Technology,Donghua University,Shanghai 201620,China)

机构地区：[1]东华大学信息科学与技术学院,上海201620

出　　处：《电子科技》2020年第8期10-15,52,共7页Electronic Science and Technology

基　　金：国家自然科学基金(61305081,61104154);上海市自然科学基金(16ZR1401300,16ZR1401200)。

摘　　要：传统TSTKS算法是一种离线突变点检测算法,该算法在待检测数据存在多个突变点时准确度较低。针对这一问题,文中结合TSTKS算法与滑动窗口理论,提出了一种快速时序数据突变点在线检测方法。该方法利用滑动窗口的思想将待检测数据切分为若干子段,并根据窗口顺序对每个子段采用TSTKS算法进行突变点检测,进而实现时序数据多突变点快速检测。实验结果表明,相比于常见的几种突变点检测算法,采用文中提出算法对存在多突变点的时序数据进行检测时耗时较少,相对误差率较低且命中率较高。The traditional TSTKS algorithm is an offline mutation point detection algorithm,which has low accuracy when there are multiple mutation points in the time series data.To solve this problem,TSTKS algorithm and sliding window theory were combined to propose an online detection method for fast time series data mutation points.The method used sliding window to divide the data into several sub-segments,and took TSTKS algorithm to detect the mutation point for each sub-segment according to the order of window,so as to realize the rapid multi-mutation points detection of time series data.The results showed that compared with the common algorithms,the proposed algorithm took less time,had lower relative error rate and higher hit rate in multiple mutation points detection.

关 键 词：TSTKS算法 突变点检测 三叉搜索树 滑动窗口理论 时序数据 在线检测 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]