Time Series: How Unusual Local Behavior Can Be Recognized Using Fuzzy Modeling Methods
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Publication:5126379
DOI10.1007/978-3-030-45619-1_13zbMath1451.62172OpenAlexW3038003293MaRDI QIDQ5126379
Publication date: 16 October 2020
Published in: Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-030-45619-1_13
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and fuzziness (62M86) Statistical aspects of big data and data science (62R07)
Cites Work
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- Mining information from time series in the form of sentences of natural language
- Towards a higher degree \(F\)-transform
- Fuzzy transforms of higher order approximate derivatives: A theorem
- Filtering out high frequencies in time series using F-transform
- A comprehensive theory of trichotomous evaluative linguistic expressions
- Linguistic characterization of time series
- Multivariate fuzzy transform of complex-valued functions determined by monomial basis
- Polynomial alias higher degree fuzzy transform of complex-valued functions
- Detection of structural breaks in linear dynamic panel data models
- Evaluative linguistic expressions vs. fuzzy categories
- Fuzzy transforms: theory and applications
- On modelling with words
- Insight into Fuzzy Modeling
- Suppression of High Frequencies in Time Series Using Fuzzy Transform of Higher Degree
- Detection of Multiple Structural Breaks in Multivariate Time Series
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