PARAMETER ESTIMATION FOR THE TRUNCATED KdV MODEL THROUGH A DIRECT FILTER METHOD

Hui Sun, Nicholas J. Moore, Feng Bao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this work, we develop a computational method to provide real-time detection for water bottom topography based on observations on surface measurements, and we design an inverse problem to achieve this task. The forward model that we use to describe the feature of the water surface is the truncated Korteweg–de Vries equation, and we formulate the inversion mechanism as an online parameter estimation problem, which is solved by a direct filter method. Numerical experiments are carried out to show that our method can effectively detect abrupt changes of water depth.

Original languageEnglish
Pages (from-to)109-132
Number of pages24
JournalJournal of Machine Learning for Modeling and Computing
Volume4
Issue number1
DOIs
Publication statusPublished - 2023
Externally publishedYes

Keywords

  • data assimilation
  • inverse problem
  • KdV equation
  • parameter estimation
  • particle filtering

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