Abstract
In the world of sensors, the importance of the timestamped data—the time series—, is increasing day by day. There are different kind of analysis techniques to handle and examine its internal structure or the relationships between them. However, the complexity and the depth of the examinations depend not only on the applied analysis methods, but also on the completeness of the used input data. In practice, the other important question is the reliability of the results. From analytical point of view, our current research focuses on the study of the correlations between time series. We recommend a complex framework with three main modules to extend the sphere of the input time series based on a systematic approach and examine the reliability of the discovered correlations.
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Acknowledgments
The research was supported by the project No. 2019-1.3.1-KK-2019-00011 financed by the National Research, Development and Innovation Fund of Hungary under the Establishment of Competence Centers, Development of Research Infrastructure Programme funding scheme.
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Pödör, Z., Bencsik, G. (2023). New Research Methodology to Analyze Time Series and Correlations’ Reliability. In: Laouar, M.R., Balas, V.E., Lejdel, B., Eom, S., Boudia, M.A. (eds) 12th International Conference on Information Systems and Advanced Technologies “ICISAT 2022”. ICISAT 2022. Lecture Notes in Networks and Systems, vol 624. Springer, Cham. https://doi.org/10.1007/978-3-031-25344-7_17
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DOI: https://doi.org/10.1007/978-3-031-25344-7_17
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