RECOGNITION OF ANOMALIES FROM TIME SERIES BY FUZZY LOGIC METHODS
Abstract and keywords
Abstract (English):
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.

Keywords:
fuzzy logic, anomaly, rectification, recognition.
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