(A) modified CUSUM (MCUSUM) algorithm for gradual change detection in a time series data시계열 데이터의 점진적 변화 감지를 위한 Modified CUSUM 알고리즘

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dc.contributor.advisorShin, Ha Yong-
dc.contributor.advisor신하용-
dc.contributor.advisorLee, Tae Sik-
dc.contributor.advisor이태식-
dc.contributor.authorJorry, Victoria Siriaki-
dc.date.accessioned2018-06-20T06:18:06Z-
dc.date.available2018-06-20T06:18:06Z-
dc.date.issued2017-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=718606&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/243039-
dc.description학위논문(석사) - 한국과학기술원 : 산업및시스템공학과, 2017.8,[iv, 40 p. :]-
dc.description.abstractThe main objective in a change point detection problem is to develop algorithms for efficient detection of gradual and /or abrupt changes in the parameter distribution of a time series data. In this dissertation, we propose a Modified Cumulative Sum (MCUSUM) algorithm for the detection of the start and end time points of a gradual change in the mean value of a time series data based on the Likelihood Ratio and Maximum Likelihood principles. The design, implementation and performance of the proposed algorithm for a gradual change detection is evaluated and compared to the existing algorithms used for the detection of abrupt and /or gradual change in the process mean known as the CUSUM and Chen and Gupta (C&G) algorithms respectively, using the mean detection delay as the performance measure. The performance of the three algorithms is evaluated using Monte Carlo Simulations. In terms of the mean detection delay, the MCUSUM procedure is found to have a comparably good performance than the two existing algorithms for the detection of the two change points.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectChange-point detection▼aGradual change▼aCumulative sum algorithm▼aMean detection delay-
dc.subject변화 감지▼a점진적변화▼a누적 합산 알고리즘▼a평균 감지 지연-
dc.title(A) modified CUSUM (MCUSUM) algorithm for gradual change detection in a time series data-
dc.title.alternative시계열 데이터의 점진적 변화 감지를 위한 Modified CUSUM 알고리즘-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :산업및시스템공학과,-
dc.contributor.alternativeauthor빅토리아-
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