Modeling systems with machine learning based differential equations

P. García

Chaos, Solitons & Fractals, 2022, vol. 165, issue P2

Abstract: The prediction of behavior in dynamical systems, is frequently associated to the design of models. When a time series obtained from observing the system is available, the task can be performed by designing the model from these observations without additional assumptions or by assuming a preconceived structure in the model, with the help of additional information about the system. In the second case, it is a question of adequately combining theory with observations and subsequently optimizing the mixture.

Keywords: Time series; Continuous models; Machine learning (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:165:y:2022:i:p2:s0960077922010517

DOI: 10.1016/j.chaos.2022.112872

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