Алгоритми FLARS та виділення аномалій часових рядів - Gvishiani, A. D.; Agayan, S. M.; Bogoutdinov, Sh. R.; Tikhotski, S. A.; Hinderer, J.; Bonnin, J.; Diament, M. (The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2019)
As a rule, algorithms of recognition of time series anomalies are based on time frequency or statistical analysis . This article is devoted to detailed formal description of new fuzzy set based algorithm FLARS (Fuzzy Logic Algorithm for Recognition of Signals). It recognizes time series anomalies by means "smooth" modelling (in fuzzy mathematics sense) of interpreter's logic, which searches for anomalies at the record.