Online state and time‐varying parameter estimation using the implicit equal‐weights particle filter Article Swipe
Mineto Satoh
,
Peter Jan van Leeuwen
,
S. Nakano
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/qj.4698
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/qj.4698
A method is proposed for resilient and efficient estimation of the states and time‐varying parameters in nonlinear high‐dimensional systems through a sequential data assimilation process. The importance of estimating time‐varying parameters lies not only in improving prediction accuracy but also in determining when model characteristics change. We propose a particle‐filter‐based method that incorporates nudging techniques inspired by optimization algorithms in machine learning by taking advantage of the flexibility of the proposal density in particle filtering. However, as the model resolution and number of observations increase, filter degeneracy tends to be the obstacle to implementing the particle filter. Therefore, this proposed method is combined with the implicit equal‐weights particle filter (IEWPF), in which all particle weights are equal. The method is validated using the 1000‐dimensional linear model with an additive parameter and the 1000‐dimensional Lorenz‐96 model, where the forcing term is parameterized. The method is shown to be capable of resilient and efficient parameter estimation for parameter changes over time in our application with a linear observation operator. This leads to the conjecture that it applies to realistic geophysical, climate, and other problems.
Related Topics
Concepts
Data assimilation
Parameterized complexity
Particle filter
Filter (signal processing)
Degeneracy (biology)
Nonlinear system
Computer science
Algorithm
Operator (biology)
Auxiliary particle filter
Mathematics
Applied mathematics
Ensemble Kalman filter
Mathematical optimization
Control theory (sociology)
Meteorology
Kalman filter
Artificial intelligence
Physics
Extended Kalman filter
Bioinformatics
Repressor
Chemistry
Gene
Computer vision
Control (management)
Quantum mechanics
Biology
Transcription factor
Biochemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/qj.4698
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/qj.4698
- OA Status
- hybrid
- Cited By
- 3
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4393183412
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4393183412Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/qj.4698Digital Object Identifier
- Title
-
Online state and time‐varying parameter estimation using the implicit equal‐weights particle filterWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-25Full publication date if available
- Authors
-
Mineto Satoh, Peter Jan van Leeuwen, S. NakanoList of authors in order
- Landing page
-
https://doi.org/10.1002/qj.4698Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/qj.4698Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/qj.4698Direct OA link when available
- Concepts
-
Data assimilation, Parameterized complexity, Particle filter, Filter (signal processing), Degeneracy (biology), Nonlinear system, Computer science, Algorithm, Operator (biology), Auxiliary particle filter, Mathematics, Applied mathematics, Ensemble Kalman filter, Mathematical optimization, Control theory (sociology), Meteorology, Kalman filter, Artificial intelligence, Physics, Extended Kalman filter, Bioinformatics, Repressor, Chemistry, Gene, Computer vision, Control (management), Quantum mechanics, Biology, Transcription factor, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 1Per-year citation counts (last 5 years)
- References (count)
-
21Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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