Forecasting the Forced van der Pol Equation with Frequent Phase Shifts Using Reservoir Computing
April 23, 2024 Β· Declared Dead Β· π Machine Learning with Applications
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Authors
Sho Kuno, Hiroshi Kori
arXiv ID
2404.14651
Category
nlin.AO
Cross-listed
cs.LG,
cs.NE
Citations
0
Venue
Machine Learning with Applications
Last Checked
3 months ago
Abstract
We tested the performance of reservoir computing (RC) in predicting the dynamics of a certain non-autonomous dynamical system. Specifically, we considered a van del Pol oscillator subjected to periodic external force with frequent phase shifts. The reservoir computer, which was trained and optimized with simulation data generated for a particular phase shift, was designed to predict the oscillation dynamics under periodic external forces with different phase shifts. The results suggest that if the training data have some complexity, it is possible to quantitatively predict the oscillation dynamics exposed to different phase shifts. The setting of this study was motivated by the problem of predicting the state of the circadian rhythm of shift workers and designing a better shift work schedule for each individual. Our results suggest that RC could be exploited for such applications.
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