An Improved Forecasting and Detection of Structural Breaks in Time Series Using Fuzzy Techniques
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-14197-3_1
Reference9 articles.
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3. Novák, V.: Detection of structural breaks in time series using fuzzy techniques. Int. J. Fuzzy Logic Intell. Syst. 18(1), 1–12 (2018)
4. Novák, V., Pavliska, V.: Time series: how unusual local behavior can be recognized using fuzzy modeling methods. In: Kreinovich, V. (ed.) Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas, pp. 157–177. Springer, Berlin (2021)
5. Novák, V., Perfilieva, I.: Non-statistical methods for analysis, forecasting and mining time series. In: Proc. 7th Int. Conference on Time Series and Forecasting. Springer (2021)
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1. Nonstatistical Methods for Analysis, Forecasting, and Mining Time Series;Contributions to Statistics;2023
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