LABVIEW IN THE RESEARCH OF FRACTAL PROPERTIES OF THE TOPOLOGY OF NETWORKS AND STOCHASTIC PROCESSES

N. Otkhozoria; Z. Azmaiparashvili; L. Petriashvili; V. Otkhozoria; E. Akhlouri

doi:10.31435/rsglobal_ws/30092023/8020

N. Otkhozoria Georgian Technical University, Tbilisi, Georgia https://orcid.org/0000-0002-5837-5345
Z. Azmaiparashvili Georgian Technical University, Tbilisi, Georgia https://orcid.org/0009-0002-5670-8326
L. Petriashvili Georgian Technical University, Tbilisi, Georgia https://orcid.org/0000-0003-3593-4877
V. Otkhozoria Georgian Technical University, Tbilisi, Georgia https://orcid.org/0009-0008-6028-3758
E. Akhlouri Georgian Technical University, Tbilisi, Georgia https://orcid.org/0009-0000-4930-4353

DOI: https://doi.org/10.31435/rsglobal_ws/30092023/8020

Keywords: Dynamic Systems, LabVIEW, Fractal Dimension, Stochastic Processes

Abstract

The advancement and utilization of computer technologies for studying and diagnosing the technical state of dynamic systems are closely linked to scientific and technological progress. Among these technologies, fractal technologies hold a prominent position [1]. Time series data, which record changes in controlled parameters over time, are commonly used for diagnosing technical objects and systems. The use of fractals will also be of interest in assessing the resonant frequency characteristics of oscillatory systems [3]. The informational characteristics of topologically distributed networks (e.g., computer, cellular) significantly depend on their geometry, node placement, and inter-node distances. The fractal dimension, a fundamental characteristic of networks, plays a crucial role in this context [2]. The research paper presents a methodology for modeling and synthesizing large networks using the node density function, which follows a power function with a fractal dimension. This characteristic aligns with Zipf's law of population distribution around urban centers. The paper also provides fractality degree indices for the network diagram. Software tools such as LabVIEW play a significant role in scientific research and experiment automation.

References

Kenneth Falconer. (2013), “Fractals: A Very Short Introduction”, Published by Oxford University Press, 138-152 pages, Paperback.

V. Butakov, A. Grakovsky (2005), “Estimation of the level of stochasticity of time series of an arbitrary origin using the Hurst exponent”. Computer Modeling and New Technologies, vol 9, #2, 27-32.

Z Azmaiparashvili, N Otkhozoria (2021) “Mathematical Model for Studying the Accuracy Characteristics of Devices for Measuring the Resonant Frequency of Oscillatory Systems New Approaches in Engineering Research” 121-131 doi.org/10.9734/bpi/naer/v5/10242D.

Chkheidze Irina, Otkhozoria Nona, Narchemashvili Medea (2023) “EVALUATION OF MEASUREMENT QUALITY USING THE MONTE-CARLO METHOD” // Universum: технические науки №3-4 (84). URL: https://cyberleninka.ru/article/n/evaluation-of-measurement-quality-using-the-monte-carlo-method.

G. Doborjginidze, L. Petriashvili (2020) “Improving efficiency of inventory identification system” EUROPEAN SCIENCE REVIEW, Premier Publishing ISSN: 2310-5577. 84-88 DOI: 10.29013/ESR-20-1.2-84-88.