Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model

E. N. Lorenz, “Deterministic nonperiodic flow,” Journal of the atmospheric sciences 20

1963

Earlier work this paper cites.

Y. Kuramoto and T. Tsuzuki, “Persistent propagation of concentration waves in dissipative media far from thermal equilibrium,” Progress of theoretical physics 55

1976

Earlier work this paper cites.

G. Sivashinsky, “Nonlinear analysis of hydrodynamic instability in laminar flames—i. derivation of basic equations,” Acta astronautica 4

1977

Earlier work this paper cites.

N. Tikhonov, Andreĭ, V. I. Arsenin, and F. John, Solutions of ill-posed problems , Vol. 14 (Winston Washington, DC, 1977)

Original

1977

Earlier work this paper cites.

D. C. Psichogios and L. H. Ungar, “A hybrid neural network-first principles approach to process modeling,” AIChE Journal 38

1992

Earlier work this paper cites.

S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural computation 9

1997

Earlier work this paper cites.

H. Jaeger, “The “echo state” approach to analysing and training recurrent neural networks-with an erratum note,” Bonn, Germany: German National Research Center for Information Technology GMD Technical Report 148

2001

Earlier work this paper cites.

W. Maass, T. Natschläger, and H. Markram, “Real-time computing without stable states: A new framework for neural computation based on perturbations,” Neural computation 14

2002

Cited alongside, same era.

H. Jaeger and H. Haas, “Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication,” science 304

2004

Cited alongside, same era.

T. Shon and J. Moon, “A hybrid machine learning approach to network anomaly detection,” Information Sciences 177

2007

Cited alongside, same era.

M. Lukoševičius and H. Jaeger, “Reservoir computing approaches to recurrent neural network training,” Computer Science Review 3

2009

Cited alongside, same era.

C.-F. Tsai and M.-L. Chen, “Credit rating by hybrid machine learning techniques,” Applied soft computing 10

2010

Cited alongside, same era.

I. Goodfellow, Y. Bengio, and A. Courville, Deep learning (MIT press, 2016)

2016

Later among the works it cites.

J. Pathak, Z. Lu, B. R. Hunt, M. Girvan, and E. Ott, “Using machine learning to replicate chaotic attractors and calculate lyapunov exponents from data,” Chaos: An Interdisciplinary Journal of Nonlinear Science 27

2017

Later among the works it cites.

L. Larger, A. Baylón-Fuentes, R. Martinenghi, V. S. Udaltsov, Y. K. Chembo, and M. Jacquot, “High-speed photonic reservoir computing using a time-delay-based architecture: Million words per second classification,” Physical Review X 7

2017

Later among the works it cites.

P. Antonik, M. Haelterman, and S. Massar, “Brain-inspired photonic signal processor for generating periodic patterns and emulating chaotic systems,” Physical Review Applied 7

2017

Later among the works it cites.