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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.18 No.1
- 발행연도
- 2018.3
- 수록면
- 1 - 12 (12page)
- DOI
- 10.5391/IJFIS.2018.18.1.1
이용수
초록· 키워드
오류제보하기
In this paper we suggest to use special “fuzzy” techniques for detection of structural breaks in time series, namely the fuzzy (F)-transform and one method of fuzzy natural logic (FNL). The idea is based on application of the F<SUP>1</SUP>-transform which makes it possible to estimate effectively slope of time series (ignoring its possible volatility) and its evaluation by a suitable evaluative linguistic expression. The method is computationally very effective.
목차
Abstract
1. Introduction
2. The Principle of F-Transform
3. Fuzzy Natural Logic
4. Time Series and F-Transform
5. Detection of Structural Breaks in Time Series
6. Conclusions
References
참고문헌 (35)
참고문헌 신청
T. C. Fu / 2011 / A review on time series data mining / Engineering Applications of Artificial Intelligence 24(1):164~181
S. De Wachter / 2012 / Detection of structural breaks in linear dynamic panel data models / Computational Statistic & Data Analysis 56(11):3020~3034
P. Preuss / 2015 / Detection of multiple structural breaks in multivariate time series / Journal of the American Statistical Association 110(510):654~668
P. Fischer / 2014 / Fast detection of structural breaks / Proceedings of the 21th International Conference on Computational Statistics :9~16
B. Doerr / 2017 / Detecting structural breaks in time series via genetic algorithms / Soft Computing 21(16):4707~4720
S. De Wachter / 2012 / Detection of structural breaks in linear dynamic panel data models / Computational Statistic & Data Analysis 56(11):3020~3034
P. Preuss / 2015 / Detection of multiple structural breaks in multivariate time series / Journal of the American Statistical Association 110(510):654~668
P. Fischer / 2014 / Fast detection of structural breaks / Proceedings of the 21th International Conference on Computational Statistics :9~16
B. Doerr / 2017 / Detecting structural breaks in time series via genetic algorithms / Soft Computing 21(16):4707~4720
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UCI(KEPA) : I410-ECN-0101-2018-003-001906827