Russian Journal of Earth Sciences Russian Journal of Earth Sciences Russian Journal of Earth Sciences 1681-1208 46671 ОРИГИНАЛЬНЫЕ СТАТЬИ ORIGINAL ARTICLES ОРИГИНАЛЬНЫЕ СТАТЬИ Recognition of anomalies from time series by fuzzy logic methods Recognition of anomalies from time series by fuzzy logic methods Gvishiani A D Gvishiani A D Agayan S M Agayan S M Bogoutdinov Sh R Bogoutdinov Sh R Graeva E M Graeva E M Zlotnicki J Zlotnicki J Bonnin J Bonnin J Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Geophysical Center, Russian Academy of Sciences, Moscow, Russia ru Observatoire de Physique du Globe, Clermont-Ferrand, France ru Observatoire de Physique du Globe, Clermont-Ferrand, France ru L'Institut de Physique du Globe de Strasbourg, Strasbourg, France ru L'Institut de Physique du Globe de Strasbourg, Strasbourg, France ru 10 1 1 9 29 10 2021 https://rjes.ru/en/nauka/article/46671/view

This paper is devoted to the detection of anomalies by the fuzzy comparison algorithm for recognition of signals (FCARS). The algorithm is a result of soft (based on fuzzy mathematics) modeling of interpreter's logic and continues in this direction the difference recognition algorithm for signals (DRAS) and the fuzzy logic algorithm for recognition of signals (FLARS), previously developed by the authors. A characteristic feature of FCARS is a more comprehensive use of the so-called fuzzy comparisons introduced by the authors. This makes FCARS more versatile and adaptive than DRAS and FLARS.

This paper is devoted to the detection of anomalies by the fuzzy comparison algorithm for recognition of signals (FCARS). The algorithm is a result of soft (based on fuzzy mathematics) modeling of interpreter's logic and continues in this direction the difference recognition algorithm for signals (DRAS) and the fuzzy logic algorithm for recognition of signals (FLARS), previously developed by the authors. A characteristic feature of FCARS is a more comprehensive use of the so-called fuzzy comparisons introduced by the authors. This makes FCARS more versatile and adaptive than DRAS and FLARS.

 fuzzy logic anomaly rectification recognition. fuzzy logic anomaly rectification recognition.

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