Diagnosing the stability of large-scale processes using fractal structure analysis of time series
DOI:
https://doi.org/10.46299/j.isjea.20240304.03Keywords:
Fractal analysis, Hurst exponent, time series, large-scale processes, stability diagnosis, non-periodic cycles, long-term memoryAbstract
This paper aims to study large-scale processes that persist over time to describe their stability, and to monitor and diagnose negative changes. By utilizing fractal structure analysis of time series, the research investigates the applicability of the Hurst exponent in diagnosing the stability of various natural and man-made systems. The findings highlight the limitations of standard Gaussian statistics and the effectiveness of fractal analysis in revealing hidden patterns and long-term dependencies in complex systems.References
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Copyright (c) 2024 Nodar Abelashvili, Nona Otkhozoria, Vano Otkhozoria, Eka Akhlouri
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