Data clustering in anomalies detection tasks based on orthogonal filters

A.V. Skatkov1, Y.E. Shishkin1,2

1 Federal State Educational Institution of Higher Education «Sevastopol State University»,

Russian Federation, Sevastopol, Universitetskaya St., 33

2 Institute of Natural and Technical Systems, Russian Federation, Sevastopol, Lenin St., 28


DOI: 10.33075/2220-5861-2018-1-36-43

UDC 004.942:004.75


   An approach to solve the problem of anomalies operative detection in monitoring data using adaptive digital filtering based on an orthogonal filter using FFT decomposition is proposed. A mathematical simulation and a real-time clustering procedure was performed. The work of the proposed approach is exemplified by the sampling Sevastopol water area sampling data using a hydrological SVP probe.

Keywords: monitoring, mathematical modeling, Big Data, digital filtering, discrete Fourier transform, detection of anomalies, clustering, critical systems, data mining.

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