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RESEARCH PRODUCT
Persistence in complex systems
S. Salcedo-sanzD. Casillas-pérezJ. Del SerC. Casanova-mateoL. CuadraM. PilesG. Camps-vallssubject
fractal dimensionFOS: Computer and information sciencesComplex systemsRenewable energyglobal solar-radiationsystems' statesComplex networksGeneral Physics and AstronomyFOS: Physical scienceslong-term and short-term methodsadaptationzero-temperature dynamicsDynamical Systems (math.DS)Physics - GeophysicsneurosciencememoryMethodology (stat.ME)PersistenceOptimization and planningMemoryMachine learningearthquake magnitude seriesFOS: MathematicsAtmosphere and climateMathematics - Dynamical SystemsAdaptationcomplex systemslow-visibility eventstime-seriesStatistics - Methodologyinflation persistenceLong-term and short-term methodsdetrended fluctuation analysislong-range correlationspersistencecomplex networksSystems’ statesEconomyneural networksrenewable energyGeophysics (physics.geo-ph)atmosphere and climateeconomymachine learningoptimization and planningNeural networkswind-speedNeurosciencedescription
Persistence is an important characteristic of many complex systems in nature, related to how long the system remains at a certain state before changing to a different one. The study of complex systems' persistence involves different definitions and uses different techniques, depending on whether short-term or long-term persistence is considered. In this paper we discuss the most important definitions, concepts, methods, literature and latest results on persistence in complex systems. Firstly, the most used definitions of persistence in short-term and long-term cases are presented. The most relevant methods to characterize persistence are then discussed in both cases. A complete literature review is also carried out. We also present and discuss some relevant results on persistence, and give empirical evidence of performance in different detailed case studies, for both short-term and long-term persistence. A perspective on the future of persistence concludes the work. This research has been partially supported by the project PID2020-115454GB-C21 of the Spanish Ministry of Science and Innovation (MICINN). This research has also been partially supported by Comunidad de Madrid, PROMINT-CM project (grant ref: P2018/EMT-4366). J. Del Ser would like to thank the Basque Government for its funding support through the EMAITEK and ELKARTEK programs (3KIA project, KK-2020/00049), as well as the consolidated research group MATHMODE (ref. T1294-19). GCV work is supported by the European Research Council (ERC) under the ERC-CoG-2014 SEDAL Consolidator grant (grant agreement 647423).
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2022-04-29 |