Communications for Statistical Applications and Methods

  • 제15권4호
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  • Pages.517-530
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  • 2008
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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삼각퍼지수를 이용한 시계열모형

Time Series Using Fuzzy Logic

  • 정혜영 (연세대학교 수학과) ;
  • 최승회 (한국항공대학교 인문자연과학부)
  • 발행 : 2008.07.16
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⟨ 이전 논문 다음 논문 ⟩

초록

본 논문은 시간의 흐름에 따라 일정한 간격으로 관측된 시계열자료에 대한 통계적인 관계를 추정하기 위하여 삼각퍼지수를 이용한 퍼지시계열모형을 소개한다. 모든 관측치를 포함하는 전체집합을 분할하는 구간을 자료의 빈도수에 따라 결정하고 연속되는 두 시점에서 퍼지수가 일치하는 경우에는 관측된 자료의 차에 대한 정보를 이용하여 제안된 퍼지시계열모형을 추정한다. 예제를 이용하여 제안된 퍼지시계열모형의 정확성을 일반적인 시계열모형과 여러 가지 방법으로 추정된 퍼지시계열모형과 비교한다.

In this paper we introduce a time series model using the triangle fuzzy numbers in order to construct a statistical relation for the data which is a sequence of observations which are ordered in time. To estimate the proposed fuzzy model we split of a universal set includes all observation into closed intervals and determine a number and length of the closed interval by the frequency of events belong to the interval. Also we forecast the data by using a difference between observations when the fuzzified numbers equal at successive times. To investigate the efficiency of the proposed model we compare the ordinal and the fuzzy time series model using examples.

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참고문헌

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