| Download | - Available on November 1, 2021
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| DOI | Resolve DOI: https://doi.org/10.1007/978-3-030-63089-8_25 |
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| Author | Search for: Valdés, Julio J.1; Search for: Céspedes-González, Yaimara; Search for: Tapping, Kenneth2; Search for: Molero-Castillo, Guillermo |
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| Name affiliation | - National Research Council of Canada. Digital Technologies
- National Research Council of Canada. Herzberg Astronomy and Astrophysics
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| Format | Text, Book chapter |
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| Book title | Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2 |
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| Series title | Advances in Intelligent Systems and Computing; Volume 1289 |
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| ISSN | 2194-5357
2194-5365 |
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| ISBN | 978-3-030-63088-1
978-3-030-63089-8 |
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| Pages | 379–392 |
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| Subject | process mining; machine learning; graph an trace clustering; fuzzy models; evolutionary multi-objective models |
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| Abstract | This paper presents a discussion of the potential of Process Mining for the analysis of general processes involving the time variation of magnitudes given by real-valued variables. These scenarios are common in a broad variety of domains, like natural and life sciences, engineering, and many others beyond business processes, where, in general, complex systems are observed and monitored using sensor data, producing time-series information. Two approaches are presented to construct event logs for such types of problems and one of them is applied to a real-world case (monitoring the F10.7 cm electromagnetic flux produced by the Sun). The results obtained with the Fuzzy Miner and the Multi-Objective Evolutionary Tree Miner algorithms successfully exposed the differences in the internal structure of the F10.7 cm series between Solar cycles. For this application, Process Mining proved to be a valuable tool for analyzing the rhythm of solar activity and how it is changing. The approach introduces here is general and could be used in the analysis of data from a broad variety of time-dependent information from many domains. |
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| Publication date | 2020-11-01 |
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| Date created | 2020-11-30 |
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| Publisher | Springer |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction |
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Record identifier | 292c8b72-091a-467a-8be3-bb3fe0499bc7 | | Record created | 2020-11-30 |
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| Record modified | 2020-11-30 |
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