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*Axioms*, Volume 12, Issue 2 (February 2023) – 130 articles

**Cover Story**(view full-size image): Structural breaks in time series are sudden unexpected changes in their course triggered by some outer cause. Unlike single outliers, they last over several time points. We have developed a non-statistical method for finding structural breaks. It applies fuzzy (F-) transform combined with methods of fuzzy natural logic (FNL). Our idea is based on the ability of the F-transform to estimate an average value of the slope in an imprecisely specified time interval and its evaluation using a specific evaluative linguistic expression whose semantics is modeled in FNL. To prove that the detected structural break can also be statistically verified, we modified the classical Chow test and showed that if a structural break is detected then it is also statistically verified. View this paper

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