Abstract
The analysis of time series of the process variables was conducted by methods of nonlinear dynamics, which allowed to determine the randomness values that are based on the depth of an object prediction. The filtering of the time series was obtained experimentally, using wavelet analysis. Defined the fractal properties of chaotic information flow, correlation dimension and the Hurst parameter were defined. The intensity of the impact of a technological parameter value on the process using Kohonen maps was identified.
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Kyshenko, V., Korobiichuk, I., Rzeplińska-Rykała, K. (2020). Technological Monitoring in the Management of the Distillation-Rectification Plant. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2019. AUTOMATION 2019. Advances in Intelligent Systems and Computing, vol 920. Springer, Cham. https://doi.org/10.1007/978-3-030-13273-6_17
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