2000 character limit reached
Sparse identification of nonlinear dynamics in the presence of library and system uncertainty (2401.13099v1)
Published 23 Jan 2024 in cs.LG and cs.AI
Abstract: The SINDy algorithm has been successfully used to identify the governing equations of dynamical systems from time series data. However, SINDy assumes the user has prior knowledge of the variables in the system and of a function library that can act as a basis for the system. In this paper, we demonstrate on real world data how the Augmented SINDy algorithm outperforms SINDy in the presence of system variable uncertainty. We then show SINDy can be further augmented to perform robustly when both kinds of uncertainty are present.
- “Discovering governing equations from data by sparse identification of nonlinear dynamical systems,” PNAS, vol. 113, no. 15, pp. 3923–3937, 2016.
- J. Horrocks and C. T. Bauch, “Algorithmic discovery of dynamic models from infectious disease data,” Scientific Reports, vol. 10, 2020.
- “Inferring biological networks by sparse identification of nonlinear dynamics,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 2, no. 1, pp. 169259–169271, 52-63.
- “Evaluation of ml algorithms for system dynamics identification of aircraft pressure control system,” PHMEC ON F, vol. 6, no. 1, pp. 7, Jun 2021.
- “Investigating sindy as a tool for causal discovery in time series signals,” in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023, pp. 1–5.
- “Basis learning for dynamical systems in the presence of incomplete scientific knowledge,” in 2023 IEEE Sixth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), Laguna Hills, CA, USA, 2023.
- Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control, Cambridge University Press, 2 edition, 2022.
- “Discovering of physics from data: Universal laws and discrepancies,” Frontiers in Artificial Intelligence, vol. 3, 2020.
- “Data-driven discovery of coordinates and governing equations,” Proceedings of the National Academy of Sciences, vol. 116, no. 45, pp. 22445–22451, 2019.
- “A unified sparse optimization framework to learn parsimonious physics-informed models from data,” IEEE Access, vol. 8, pp. 169259–169271, Jan 2020.
- “Sindy-pi: A robust algorithm for parallel implicit sparse identification of nonlinear dynamics,” Proc. R. Soc. A, vol. 476, pp. 20200279, 2020.
- “Data-driven discovery of partial differential equations,” Science Advances, vol. 3, no. 4, pp. e1602614, 2017.
- “Discovering governing equations from partial measurements with deep delay autoencoders,” Proc. R. Soc. A, vol. 479, pp. 20230422, 2023.
- Fundamentals of Ecology, Thomson Brooks/Cole, Belmont, CA, 5th edition, 2005.
- “Detecting causality in complex ecosystems,” Science, vol. 338, no. 6106, pp. 496–500, 2012.
- M. Stokes, “An introduction to managing wild game populations,” Nature Education Knowledge, vol. 2, no. 11, pp. 4, 2011.
- “Perspectives in machine learning for wildlife conservation,” Nature Communications, vol. 13, pp. 792, 2022.
- “Species replacement in marine ecosystems with reference to the california current,” Minutes of Meeting Marine Research Committee, vol. 7, no. 1, 1964.
- R. Lasker and A. MacCall, “Proceedings of the joint oceanographic assembly, halifax, august 1982: General symposia,” in Department of Fisheries and Oceans, 1983, pp. 110–120.
- “Stock-recruitment models for pacific sardine (Sardinops sagax),” Canadian Journal of Fisheries and Aquatic Sciences, vol. 52, no. 3, pp. 566–577, 1995.
- Edward Norton Lorenz, “Deterministic nonperiodic flow,” Journal of the Atmospheric Sciences, vol. 20, no. 2, pp. 130–141, 1963.
- “A contribution to the empirics of economic growth,” The Quarterly Journal of Economics, vol. 107, no. 2, pp. 407–437, 1992.
- Eugene M. Izhikevich, Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting, The MIT Press, 2010.
- Steve H. Strogatz, Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, CRC Press;, 2 edition, 2015.
- Introduction to the Theory of Complex Systems, Oxford University Press;, 2018.