STABILITY ESTIMATION OF THE DYNAMIC CLUSTERING ALGORITHM FOR TEMPERATURE SIGNALS
Y.V. Volkov
Institute of Monitoring of Climatic and Ecological Systems, Siberian Branch, Russian Academy of Sciences, Tomsk, Russia
Keywords: signals analysis, mathematical model, surface temperature, climate classification, clustering, algorithm stability estimation
Abstract
An algorithm for dynamic clustering of temperature signals, which is used to solve the problem of isolating climatic regions on the Earth surface characterized by a certain homogeneous (within the boundaries of the region) type of the climate is considered. A numerical experiment implemented to assess its stability is described. The reference signal model used in the numerical experiment is represented as a sum of harmonic components. The additive noise components are generated in the frequency domain. The parameters varied in the numerical experiment are the noise value and sample size. The estimates of the root-mean-square deviations and stability of the dynamic clustering algorithm are given.
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