Robust forecasting using predictive generalized synchronization in reservoir computing

Platt, J.A.; Wong, A.; Clark, R.; Penny, S.G.; Abarbanel, H.D.I.

doi:10.1063/5.0066013

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Robust forecasting using predictive generalized synchronization in reservoir computing

2021
By Platt, J.A. ; Wong, A. ; Clark, R. ; ...
Source: Chaos 31, 123118 (2021)

[PDF-3.16 MB]

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Journal Title:

Chaos
Personal Author:

Platt, J.A. ; Wong, A. ; Clark, R. ; Penny, S.G. ; Abarbanel, H.D.I.

Platt, J.A. ; Wong, A. ; Clark, R. ; Penny, S.G. ; Abarbanel, H.D.I. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences)

OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences) Less -
Description:

Reservoir computers (RCs) are a class of recurrent neural networks (RNNs) that can be used for forecasting the future of observed time series data. As with all RNNs, selecting the hyperparameters in the network to yield excellent forecasting presents a challenge when training on new inputs. We analyze a method based on predictive generalized synchronization (PGS) that gives direction in designing and evaluating the architecture and hyperparameters of an RC. To determine the occurrences of PGS, we rely on the auxiliary method to provide a computationally efficient pre-training test that guides hyperparameter selection. We provide a metric for evaluating the RC using the reproduction of the input system’s Lyapunov exponents that demonstrates robustness in prediction.
Keywords:

[+]

Machine Learning Neural Networks (Computer Science) Predictive Generalized Synchronization (PGS) Recurrent Neural Networks (RNNs) Reservoir Computers (RCs)
Source:

Chaos 31, 123118 (2021)
DOI:

https://doi.org/10.1063/5.0066013
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PDF
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Journal Article
Funding:

Grant no. NA18NWS4680048 ; Grant no. NA19NES4320002 ; Grant no. NA20OAR4600277

Grant no. NA18NWS4680048 ; Grant no. NA19NES4320002 ; Grant no. NA20OAR4600277 Less -
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urn:sha256:96e83b0924b8c429709cf01dae65ba6fc13f709e6be937b9d42dc6385a182774
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https://repository.library.noaa.gov/view/noaa/48975/noaa_48975_DS1.pdf
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Robust forecasting using predictive generalized synchronization in reservoir computing

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